Next Article in Journal
Integration of Computational Pipeline to Streamline Efficacious Drug Nomination and Biomarker Discovery in Glioblastoma
Previous Article in Journal
Direct Implantation of Patient Brain Tumor Cells into Matching Locations in Mouse Brains for Patient-Derived Orthotopic Xenograft Model Development
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Cancers
Volume 16
Issue 9
10.3390/cancers16091721
cancers-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles thumb_up
...
Endorse textsms
...
Comment
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Review

Textbook Neoadjuvant Outcome—Novel Composite Measure of Oncological Outcomes among Gastric Cancer Patients Undergoing Multimodal Treatment

by
Zuzanna Pelc
1,
Katarzyna Sędłak
1,
Magdalena Leśniewska
1,
Katarzyna Mielniczek
1,
Katarzyna Chawrylak
1,
Magdalena Skórzewska
1,
Tomasz Ciszewski
1,
Joanna Czechowska
1,
Agata Kiszczyńska
1,
Bas P. L. Wijnhoven
2,
Johanna W. Van Sandick
3,
Ines Gockel
4,
Suzanne S. Gisbertz
5,6,
Guillaume Piessen
7,
Clarisse Eveno
7,
Maria Bencivenga
8,
Giovanni De Manzoni
8,
Gian Luca Baiocchi
9,
Paolo Morgagni
10,
Riccardo Rosati
11,
Uberto Fumagalli Romario
12,
Andrew Davies
13,
Yutaka Endo
14,
Timothy M. Pawlik
14,
Franco Roviello
15,
Christiane Bruns
16,
Wojciech P. Polkowski
1 and
Karol Rawicz-Pruszyński
1,*add Show full author list remove Hide full author list
1
Department of Surgical Oncology, Medical University of Lublin, 20079 Lublin, Poland
2
Department of General Surgery, Erasmus Medical Center, 3015 GD Rotterdam, The Netherlands
3
Department of Surgical Oncology, The Netherlands Cancer Institute-Antoni van Leeuwenhoek Hospital, 1066 CX Amsterdam, The Netherlands
4
Department of Visceral, Transplant, Thoracic and Vascular Surgery, University Hospital Leipzig, 04103 Leipzig, Germany
5
Department of Surgery, Amsterdam UMC location University of Amsterdam, 1007 MB Amsterdam, The Netherlands
6
Cancer Treatment and Quality of Life, Cancer Center Amsterdam, 1081 HV Amsterdam, The Netherlands
7
Department of Digestive and Oncological Surgery, University Lille, and Claude Huriez University Hospital, 59000 Lille, France
8
Upper G.I. Surgery Division, University of Verona, 37126 Verona, Italy
9
Department of Clinical and Experimental Sciences, Surgical Clinic, University of Brescia, and Third Division of General Surgery, Spedali Civili di Brescia, 25123 Brescia, Italy
10
Department of General Surgery, Morgagni-Pierantoni Hospital, 47121 Forlì, Italy
11
Department of Gastrointestinal Surgery, IRCCS San Raffaele Hospital, Vita Salute University, 20132 Milan, Italy
12
Digestive Surgery, European Institute of Oncology, IRCCS, 20139 Milan, Italy
13
Department of Upper Gastrointestinal and General Surgery, Guy’s and St Thomas’ Hospital, London SE1 7EH, UK
14
Department of Surgery, The Ohio State University Wexner Medical Center and James Comprehensive Cancer Center, Columbus, OH 43210, USA
15
Department of Medicine, Surgery, and Neurosciences, University of Siena, 53100 Siena, Italy
16
Department of General, Visceral, Cancer and Transplantation Surgery, University Hospital of Cologne, 50937 Cologne, Germany
 
add Show full affiliation list
 
remove Hide full affiliation list
*
Author to whom correspondence should be addressed.
Cancers 2024, 16(9), 1721; https://doi.org/10.3390/cancers16091721
Submission received: 11 April 2024 / Revised: 26 April 2024 / Accepted: 26 April 2024 / Published: 28 April 2024
(This article belongs to the Section Clinical Research of Cancer)
Browse Figure
Versions Notes

Abstract

:

Simple Summary

This narrative review aims to present the rationale for the implementation of a novel composite measure, Textbook Neoadjuvant Outcome, among patients with gastric cancer. Textbook Neoadjuvant Outcome integrates five objective and well-established components: Treatment Toxicity, Laboratory Tests, Imaging, Time to Surgery, and Nutrition. It represents a desired, multidisciplinary care and hospitalization of gastric cancer patients undergoing neoadjuvant chemotherapy to identify the treatment- and patient-related data required to establish high-quality oncological care further.

Abstract

The incidence of gastric cancer (GC) is expected to increase to 1.77 million cases by 2040. To improve treatment outcomes, GC patients are increasingly treated with neoadjuvant chemotherapy (NAC) prior to curative-intent resection. Although NAC enhances locoregional control and comprehensive patient care, survival rates remain poor, and further investigations should establish outcomes assessment of current clinical pathways. Individually assessed parameters have served as benchmarks for treatment quality in the past decades. The Outcome4Medicine Consensus Conference underscores the inadequacy of isolated metrics, leading to increased recognition and adoption of composite measures. One of the most simple and comprehensive is the “All or None” method, which refers to an approach where a specific set of criteria must be fulfilled for an individual to achieve the overall measure. This narrative review aims to present the rationale for the implementation of a novel composite measure, Textbook Neoadjuvant Outcome (TNO). TNO integrates five objective and well-established components: Treatment Toxicity, Laboratory Tests, Imaging, Time to Surgery, and Nutrition. It represents a desired, multidisciplinary care and hospitalization of GC patients undergoing NAC to identify the treatment- and patient-related data required to establish high-quality oncological care further. A key strength of this narrative review is the clinical feasibility and research background supporting the implementation of the first and novel composite measure representing the “ideal” and holistic care among patients with locally advanced esophago-gastric junction (EGJ) and GC in the preoperative period after NAC. Further analysis will correlate clinical outcomes with the prognostic factors evaluated within the TNO framework.

1. Introduction

With an estimated annual over one million new diagnoses and 770,000 deaths worldwide in 2020, gastric cancer (GC) represents 5.6% of the global cancer incidence and is the fourth-leading cause of all cancer-related deaths [1]. Moreover, considering aging and the growth of the world population, an increase of 62% to 1.77 million cases in GC incidence by 2040 is expected [2]. In locally advanced settings, stomach neoplasms typically require multidisciplinary care. In order to facilitate margin-negative resection and improve survival, esophageal (EC) and GC patients are increasingly treated with neoadjuvant chemotherapy (NAC) prior to curative-intent resection [3].
NAC has evolved into an integral component of multidisciplinary care, contributing to improved locoregional control and comprehensive patient treatment [4]. Almost two decades ago, the MAGIC trial redefined the treatment for locally advanced GC patients by demonstrating a substantial increase in 5-year survival with the addition of perioperative chemotherapy to surgery [5]. Since the MAGIC trial, the role of NAC has been further established with the introduction of the FLOT regimen (Fluorouracil, Leucovorin, Oxaliplatin, and Docetaxel) improving the median overall survival (OS) from 36 to 50 months (HR 0.77; 95% CI: 0.63–0.94) [6]. The role of radiotherapy requires further exploration, as the results from the ARTIST and ARTIST-II trials failed to support its addition in the adjuvant setting, even for patients with lymph-node-positive disease [7,8]. The ongoing phase III TOP GEAR (Trial Of Preoperative therapy for Gastric and Esophagogastric junction AdenocaRcinoma) aims to determine whether neoadjuvant radiotherapy, in combination with perioperative epirubicin/cisplatin/fluorouracil (ECF) chemotherapy, proves superior to perioperative ECF regimen alone [9].
Currently, data supporting the implementation of NAC extend to subsequent gastrointestinal malignancies. Although preoperative radiochemotherapy (41.4 Gy radiotherapy plus carboplatin/paclitaxel, CROSS regimen) has been the gold standard for EC treatment for over a decade, a recent analysis comparing FLOT and CROSS regimens revealed non-inferiority of perioperative chemotherapy, a treatment modality reflecting modern benchmarks of oncologic safety [10]. In the NEO-AEGIS trial, the MAGIC regimen (Epirubicin, Cisplatin, and 5-FU or Capecitabine) was primarily also included in the analysis [11]. Despite the initial assumption of 10% superiority of the CROSS regimen, a futility analysis led to a modification, requiring 5% non-inferiority for perioperative chemotherapy. The results supported clinical equivalence, demonstrating no differences in morbidity, quality of life (QoL), and the 3-year survival probability between CROSS and FLOT/MAGIC arms (HR 1.03, 95% CI 0.77–1.38) [11]. The awaited results of the ESOPEC trial will further evaluate whether FLOT provides survival benefits over CROSS among EC patients [12].
Individually assessed parameters have served as surrogate benchmarks for treatment quality in the past decades [13]. As such, lymph node harvest and R0 resection, surgical quality indicators, impact long-term prognosis and the risk of disease recurrence [14]. While National Comprehensive Cancer Network (NCCN) guidelines recommend the dissection of a minimum of 15 lymph nodes [14], recent data suggest that harvesting at least 23 lymph nodes improves both pathological nodal staging and 5-year survival [15]. However, the optimal nodal yield after NAC is debated, especially considering the stage migration phenomenon, which refers to the relationship between the number of dissected lymph nodes and survival [16]. Corresponding to the evidence from the East [16], the Surveillance, Epidemiology, and End Results (SEER) registry analysis suggested prolonged survival following a greater extent of lymph node dissection [17]. However, Western observations questioned these findings, as more advanced N stage corresponds with tumor burden, and more aggressive lymphadenectomy may result in major surgical trauma [18]. Differences also apply to R0 resection, and despite a unified definition, survival outcomes vary significantly between Eastern and Western centers [19].
Recently, the Outcome4Medicine Consensus Conference, a group dedicated to assessing outcomes in medical interventions, has highlighted the inadequacy of solely examining isolated metrics [13]. This approach fails to fully provide a picture of overall quality and capture the complexity of the clinical scenario. In response to the limitations associated with this singular approach, the adoption of composite measures has gained increased acknowledgment, emphasizing the significance of integrating data from various domains [13]. One of the most simple and comprehensive is the “All or None” method, which refers to an approach where a specific set of criteria must be fulfilled for an individual to be considered as achieving the overall measure [20]. Textbook Outcome (TO) emerged as a comprehensive surgical quality metric, which focuses on desired post-operative outcomes and an ideal hospitalization, representing the multidimensional aspects of the complete surgical pathway. TO not only serves as a prognostic factor but also successfully represents real-world data in a more holistic manner [21,22].
A recently proposed modification of TO among GC patients, Textbook Oncological Outcome (TOO), integrates compliance with perioperative chemotherapy into the standard definition of TO, allowing for a more complex assessment of multimodal oncology care [23]. The analysis of patients with locally advanced GC in Europe revealed a 33% improvement in TO achievement with the implementation of NAC. Although overall TO was achieved in 68.5% of cases, chemotherapy compliance was observed in only 30.8%, resulting in a decreased TOO accomplishment (22.8%). The observed disparity highlights the existing dissonance in evaluating the precisely defined specific components of surgery and NAC, in which the assessment primarily focuses on whether the treatment is administered or not.
Along with the clinical importance of NAC, optimizing QoL and patient-reported outcomes (PROs) during multidisciplinary cancer care is important to patients and healthcare providers. As data on patient-centered outcomes remain scarce [3], designing patient-centered strategies aiming at preventing attrition during NAC remains crucial [24,25].
Consequently, the aim of this narrative review is to present the rationale for the implementation of a novel composite measure, Textbook Neoadjuvant Outcome (TNO). TNO seeks to reflect a desired, multidisciplinary care and hospitalization of selected upper gastrointestinal malignancies. Specifically, we focus on outcomes for NAC among patients with locally advanced esophago-gastric junction (EGJ) cancer and GC undergoing curative-intent treatment to identify the treatment- and patient-related data required to establish high-quality oncological care furthermore.

2. Exploring TNO Components

TNO, designed as an ‘All or None’ composite measure, integrates five objective, well-established, and reproducible components depicted in Figure 1. The fulfillment of each criterion equals TNO achievement, while failure to meet any disqualifies its accomplishment. Each parameter should be assessed during the period between the last NAC cycle and the surgery. The subsequent discussion presents the rationale behind the inclusion of each component in the TNO measure, while the study path is depicted in Supplementary Figure S1.

3. Treatment Toxicity

Treatment toxicity, particularly in the context of NAC, can be a critical consideration against preoperative chemotherapy administration [5,26]. Although most studies do not show an increase in postoperative complications, the potential adverse effects (AEs) of NAC may pose challenges to the success of multimodal therapy adherence. As reported in the CRITICS trial, which evaluated the outcomes following NAC in a Western population of locally advanced GC, up to 85% of patients had to discontinue preoperative treatment due to its toxicity, doubling the risk of perioperative complications [27]. Moreover, in the FLOT4-AIO trial, 25% of patients in the FLOT cohort experienced at least one serious adverse event (AE) related to medical or surgical complications [6]. The percentage of patients discontinuing chemotherapy due to FLOT-related side effects surpassed 40%. Notably, among various reasons for perioperative chemotherapy disruption, only 60 (40.5%) patients in the experimental arm completed the planned 8 cycles of systemic treatment out of 148 initially randomized individuals.
While certain reports question the association between NAC toxicity and subsequent treatment outcomes [28,29], there remains an underrepresentation of docetaxel-based regimens. Yet, the FLOT scheme has been recommended as first-line perioperative chemotherapy among locally advanced GC patients in both NCCN and European Society of Medical Oncology (ESMO) guidelines [14,30]. Meanwhile, the most common AEs associated with FLOT are well-documented and include a range of gastrointestinal, hematological, and neurological side effects [6]. Thus, monitoring of toxicities during NAC is crucial to promptly address and manage potential complications, optimize patient well-being, and ensure treatment adherence.
For reporting toxicity, the Common Terminology Criteria for Adverse Events (CTCAE) are used. CTCAE represents the gold standard for classifying and grading the severity of AEs in cancer therapy, clinical trials, and various oncology settings [31]. Employing descriptive terminology, CTCAE provides a grading scale for each adverse event term, offering a systematic and widely accepted approach to reporting and assessing the impact of medical treatments or procedures (Table 1). This comprehensive tool ensures a standardized evaluation of AEs, enhancing communication and facilitating a clearer understanding of their clinical significance.
Addressing and mitigating treatment toxicity is important to optimize the overall success of treatment in the management of GC patients undergoing multimodal therapy. Therefore, we advocate for the incorporation of the latest 5th edition of CTCAE into the assessment of NAC outcomes. Specifically, we propose the inclusion of Grade 1 and Grade 2 toxicity, indicating mild effects that require no or non-urgent medical interventions or therapy, as an additional integral element of the TNO measure.

4. Laboratory Tests

Systemic inflammatory response has been established as a significant clinical tool and a prognostic factor associated with adverse outcomes in various malignancies [33,34]. Particularly in GC, a correlation between local inflammation and tumor growth exists [4]. Chronic infection stimulates the development of inflammatory micro-environment and promotes further progression and metastasis of the disease. Recognizing the need for a comprehensive tool including both the impact of inflammation on GC prognosis and a reliable predictive factor, numerous immuno-inflammatory markers have been developed presenting diverse outcomes and distinctive advantages [33,35,36,37]. Among them, arising from complete blood count measurements, the Neutrophil-to-Lymphocyte (NLR) ratio is a well-established prognostic and predictive marker for diverse Asian and European GC populations, evaluated not only before surgery alone, but more significantly, also in the post-NAC setting [35,36,38,39,40]. The preoperative NLR, traditionally recognized as the predictor of long-term outcomes, is increasingly acknowledged for its potential utility in prognosticating short-term outcomes and disease-free survival, particularly in advanced GC patients [41]. Meanwhile, Platelet-to-Lymphocyte Ratio (PLR) [42], Lymphocyte-to-Monocyte Ratio (LMR) [39], Inflammatory Burden Index (IBI) [43], and Prognostic Nutritional Index (PNI) [33] have demonstrated different results in predicting Overall Survival (OS) and risk factors, each presenting unique advantages and limitations in different patient populations (Table 2).
While future considerations may highlight molecular markers like microsatellite instability microsatellite instability (MSI) as a potentially superior predictive tool, its restricted integration into clinical practice due to time and cost limitations contrasts with the simplicity and accessibility of NLR [44]. The cutoff value of NLR ≤ 2 has been suggested as it represents a balance between sensitivity and specificity, providing a practical and clinically relevant threshold for distinguishing between patients with different prognostic outcomes. Therefore, we recommend incorporating NLR ≤ 2 into TNO, serving as a crucial marker for estimating the inflammatory burden in GC patients and its consequential effects on treatment outcomes.
Table 2. Summary of Key Inflammatory Markers in GC Patients.
Table 2. Summary of Key Inflammatory Markers in GC Patients.
Inflammatory Marker Study PopulationResults Distinctive AdvantagesLimitations
NLRPost-hoc exploratory analysis of REAL-2 RCT [35]
Retrospective analysis [39]		908 advanced AEG cancer patients undergoing multimodal treatment from UK and Australia
106 locally advanced GC patients 		High NLR associated with OS (HR = 1.73, 1.50–2.00)
High NLR associated with OS (HR = 1.94, 1.02–3.70)		Predictive factor of short- and long-term outcomes [41], peritoneal and/or metastatic disease [40]
Independent prognostic factor in multimodal treatment 		Underrepresentation of the population with poor performance status due RCT design
Relatively small sample size
PLRMeta-analysis of 8 studies [42] 4513 GC patients undergoing upfront surgery High PLR not a reliable predictor for OS (HR = 0.99, 95% CI: 0.9–1.1)High PLR correlated with a higher risk of LN metastasis and serosal invasion Not a negative predictor for OS
LMRRetrospective analysis [39] 106 locally advanced GC patients undergoing NACHigh LMR not a reliable predictor for OS (HR = 0.92, 95% CI: 0.47–1.79)Reassessment of LMR at post-12-month might be helpful in predicting the long-term survival [45]Lack of prognostic and predictive role in European population undergoing NAC
IBIRetrospective analysis [43] 6359 cancer patientsHigh IBI associated with physical condition, malnutrition, cachexia, and short-term outcomes; independent risk factor (HR = 1.114; 95% CI, 1.072–1.157)Combined value of NLR and CRP Asian population, little data regarding GC patients [46]
GPS, mGPSRetrospective analysis [37]1710 GC patients undergoing curative or palliative surgery mGPS associated with postoperative mortality (OR, 1.845; 95% CI, 1.184–2.875)Indicator of nutritional status, different prognostic value of mGPS depending on tumor stageJapanese population, prognostic significance of GPS in GC has not been fully investigated
PNITwo-institutional retrospective analysis [33] 206 AEG and UGC patients undergoing curative-intent surgery Predictive factor of OS (HR =
8.946) and RFS (HR = 6.416)		Indicator of nutritional statusAsian population, cohort limited to upper GC patients, no assessment after NAC
NLR—Neutrophil-to-Lymphocyte Ratio; PLR—Platelet-to-Lymphocyte Ratio; LMR—Lymphocyte-to-Monocyte Ratio; IBI—Inflammation Burden Index, GPS—Glasgow Prognostic Score; mGPS—modified Glasgow Prognostic Score; PNI—Prognostic Nutritional Index; RCT—Randomized Controlled Trial; AEG—Adenocarcinoma of the EsophaGogastric junction, UGC—Upper Gastric Cancer; GC—Gastric Cancer; NAC—Neoadjuvant Chemotherapy; OS—Overall Survival; HR—Hazard Ratio; CI—Confidence Interval; OR—Odds Ratio; RFS—Recurrence Free Survival; CRP—C-Reactive Protein.

5. Radiological Evaluation

Imaging plays a significant role in evaluating tumor response to systemic treatment. Apart from an objective in vivo assessment of disease burden, it allows for determining whether NAC should be pursued, adjusted, or interrupted [47]. According to the ESMO, NCCN, and Japanese Gastric Cancer Treatment guidelines, computed tomography (CT) scanning is routinely used for preoperative staging among GC patients [14,30,48]. Given the increasing role of multimodal therapy in locally advanced settings, the need for a common approach and systematic response assessment in GC is paramount [49]. For over two decades, Response Evaluation Criteria in Solid Tumors (RECIST and RECIST 1.1) have been the standard for response assessment in numerous malignancies, including GC. Objective tumor response for target lesions is determined based on the following criteria: Complete Response (CR): disappearance of all target lesions, with any pathological lymph node diameter < 10 mm in short axis; Partial Response (PR): at least a 30% decrease in the sum of diameters of target lesions, taking as reference the baseline sum diameters; Progressive Disease (PD): at least a 20% increase in the sum of diameters of target lesions, taking as reference the smallest sum on study, as well as appearance of one or more new lesions; Stable Disease (SD): neither sufficient shrinkage to qualify for PR nor sufficient increase to qualify for PD, taking as reference the smallest sum diameters [50]. Since RECIST has been a method of choice in standardized tumor response evaluation among the vast majority of clinical trials, it allows an evidence-based tumor workup in the multimodal setting [51]. Although the criteria are not organ-specific and might not evaluate the critical parameters associated with survival outcomes in specific cancer types and treatments, the RECIST-based endpoint of response rate seems to provide simplicity, availability, cost-effectiveness, and intuitiveness in locally advanced GC [47].
Another limitation of CT arises from the low sensitivity in detecting lymph node metastases, a wide range of sensitivity (23–76%) in diagnosing peritoneal spread, and the preservation of only 1% of unnecessary laparotomies based on restaging CT scans [52]. Possibly, with the advancement of computing power and graphic processing technologies [53], artificial intelligence (AI) techniques demonstrate the potential to enhance CT by providing more accurate staging and restaging of the GC along with improved detection of recurrence and progression of the disease [54]. To address shortcomings of CT, staging laparoscopy (SL) is a recommended complementary diagnostic method in potentially resectable GC, preventing 25% of irrelevant gastrectomies [14,55]. Although SL has limited abdominal cavity exploration, the procedure yield exceeds 36%, with lavage cytology further improving the detection of radiologically occult peritoneal metastasis [56,57]. Moreover, SL maintains its sensitivity independently of lymph node involvement, and its yield has remained consistent over time despite improvements in imaging techniques. A recent Systematic Review indicated a high heterogeneity in procedure technique [55], and there is no consensus on whether to perform repeated SL after NAC as well. However, given the increased rate of minimally invasive gastrectomy in the West, performing laparoscopy with intraoperative decision to pursue with curative intent gastrectomy, may condition further assessment of surgical textbook outcomes. SL could be considered as a “bridge to cross to TO”, facilitating the transition from neoadjuvant assessment to the comprehensive evaluation of surgical outcomes.
Despite the limited prognostic value of strict radiological downstaging when comparing baseline and post-NAC CT among locally advanced GC patients from the West [58], we suggest including no PD as a radiological component of TNO. An acceptable alternative to restaging CT is the intraoperative assessment of disease burden at the initial stage of surgical procedure, providing a complementary and potentially more accurate evaluation of treatment response.

6. Nutrition

Almost 20% of cancer-related deaths are caused by malnutrition rather than malignancy itself, with up to 40% of malnourished patients being misdiagnosed [59,60]. Gastrointestinal cancer patients are especially at high risk of developing malnutrition, with prevalence rates ranging from 30% to 80% [61].
The European Society for Clinical Nutrition and Metabolism (ESPEN) recommends Nutrition Risk Screening-2002 (NRS-2002) and the Malnutrition Universal Screening Tool (MUST) for malnutritional risk screening in the general population, and Mini Nutritional Assessment (MNA) for geriatric patients [62]. However, the application of these tools is confined to prescreening and identifying patients “at nutritional risk”, a condition associated with increased morbidity and mortality. To confirm the malnutrition diagnosis and perform a nutritional status assessment, ESPEN specifies the fulfillment of one of the following criteria: body mass index (BMI) < 18.5 kg/m2, reduced BMI accompanied by weight loss, or decreased fat-free mass index (FFMI) [62]. Although weight loss within a defined timeframe is a straightforward approach in research and routine oncology practice, it is considered unimodal and oversimplified, insufficient to solely use to diagnose malnutrition [63]. The exclusive assessment of BMI holds superior diagnostic value compared to weight loss, with BMI being the only prognostic factor among ESPEN criteria for patients with gastrointestinal cancers [62,64].
Nonetheless, it is crucial to recognize the limitations within this approach as malnutrition occurs independently of initial body weight and obesity does not exclude the concurrent diagnosis of sarcopenia or cachexia [63]. While the negative impact of underweight as a prognostic factor has been well-established, the landscape of overweight remains more complex and inconclusive [61,63]. Apart from the “obesity paradox”, the phenomenon of lower mortality associated with increased weight is explained by potential selection bias; even more than 60% of gastrointestinal cancer patients with excessive body mass will develop malnutrition [63,65]. This group of patients often remains overlooked in routine nutritional screening; meanwhile, silently developed cachexia or sarcopenia leads to poor prognosis and decreased survival [66].
Patients undergoing NAC represent another distinct group requiring a specific nutritional approach. The preoperative period remains clinically significant for the implementation of prehabilitation—a comprehensive approach that combines physical and nutritional therapy [67]. The main objective is to optimize patients’ fitness and prepare them for metabolic stress and surgical trauma, thereby enhancing adherence to perioperative chemotherapy. A systematic review of randomized controlled trials of prehabilitation incorporated a range of exercise training and psychological and nutritional interventions with diverse effectiveness [68]. Despite the absence of a standardized protocol, this multifaceted approach proves non-inferior to the established standard of care and merits consideration as an integral component of contemporary patient-centered healthcare.
Another interesting concept is frailty, a multidimensional syndrome often accompanied by malnutrition and sarcopenia, which represents decreased physiologic reserve and ability to recover from different stressors [69]. Frailty is a dynamic state that mirrors biological age, influenced by conditions such as comorbidities or social determinants of health. Frail GC patients are at significantly higher risk of mortality (6.83 vs. 3.50%), morbidity (3.42 vs. 0.94%), and prolonged length of stay (16.7 vs. 12.0 days) when compared with non-frail individuals [70]. While the concept is promising, the National Surgical Quality Improvement Program (NSQIP), established by the American College of Surgeons, has emphasized the need for additional efforts in defining and assessing frailty [69,71].
Specific nutritional strategies to overcome body composition deficiencies are recommended, aligning with Enhanced Recovery After Surgery (ERAS) principles [72]. Unlike conventional perioperative approaches, ERAS integrates cutting-edge techniques in anesthesiology, pain management, nutrition, psychology, and surgery, combining them with traditional methods to enhance postoperative recovery. It is estimated that even 65% of surgical patients present some degree of malnutrition, and adherence to ERAS protocol improved 5-year survival in colorectal cancer patients correlated with early nutritional delivery in the postoperative period [73]. However, its adoption in gastrointestinal surgery remains underrepresented, largely due to distinct traditional post-gastrectomy management practices [74]. Additionally, the impact of ERAS is evaluated after the surgery, and the tool assessing patients’ condition in the post-NAC setting is lacking.
Given that both excessive- and underweight status not only enhance treatment-related toxicity but also significantly increase mortality rates, it is crucial to assess the nutritional status of patients with gastrointestinal malignancies at the early stages of oncologic treatment in a simple and widely accepted manner [66,75,76]. Therefore, evaluating and addressing the nutritional status of patients within TNO through BMI seems beneficial and an applicable method to optimize treatment outcomes, including NAC tolerability. Based on the World Health Organization (WHO) [77] we adopt BMI ranging from 18.5 to 24.9 kg/m2 as one of the components of TNO.

7. Time to Surgery

Since NAC potentially allows for primary tumor downstaging and may contribute to the clearance of clinically occult nodal- and micro-metastases, it is important to determine factors increasing the likelihood of pathologic response (PR), ultimately resulting in improved OS [6]. Association between completion of preoperative therapy and time to surgery (TTS) has been suggested as one of the factors influencing the PR in several gastrointestinal malignancies. While a prolonged (6–8 week) interval between neoadjuvant radiotherapy and surgery showed increased tumor downstaging with no detrimental effect on toxicity in rectal cancer [78,79], breast cancer patients undergoing surgery within three weeks after completion of NAC experienced improved survival outcomes, with TTS being an independent prognostic factor, even among patients with complete PR [80]. However, in EC patients undergoing preoperative radiochemotherapy, TTS exceeding 6 weeks negatively impacted survival with no significant improvement in PR, tumor regression, or radicality of resection [81].
A recent meta-analysis of retrospective observational studies that included 1171 patients undergoing gastrectomy after NAC within three timeframes—4–6 weeks, <4 weeks, and >6 weeks—reported comparable outcomes in terms of complete PR, R0 resection rate, and the incidence of serious postoperative complications, as well as 3-year progression-free survival (PFS) and OS [82]. A subsequent meta-analysis compared patient outcomes between TTS within 4–6 weeks and 4–6 weeks after NAC completion among patients with locally advanced GC [83]. Pooled data were not associated with significant differences in major and complete PR rates, ypN0, postoperative complications, R0 resection rates, and operative time between groups of longer TTS and shorter TTS. However, when taking into account the Western population, the highest rate of major PR was achieved in patients undergoing gastrectomy within 4 weeks after NAC completion compared with individuals receiving surgical treatment within 4–6 weeks or later [84]. Furthermore, shorter TTS was associated with similar postoperative morbidity and mortality. At the same time, additional medical optimization in preparation for surgery may offer benefits without impacting outcomes or nodal upstaging [85]. Although large-scale prospective randomized controlled trials are warranted to establish optimal TTS among locally advanced GC patients undergoing multimodal treatment, we suggest a 4–6 week time interval to gastrectomy after NAC as a TNO component.

8. Systemic Therapy

In recent years, the treatment landscape of GC has undergone significant evolution, primarily driven by the introduction of novel immunotherapies and targeted treatment options applicable across diverse disease stages [4,30]. Following these advancements, a noticeable shift has been observed towards an individualized approach and biomarker-tailored treatments, particularly in the metastatic setting. However, for locally advanced disease, perioperative chemotherapy and curatively-intended surgery remain the cornerstone of sustainable cancer treatment [14].
The administration of chemotherapy before surgical management offers both apparent and more subtle benefits [44]. Chemotherapeutic agents are delivered to the primary site before surgical vasculature disruption more efficiently. Apart from downstaging the primary tumor and increasing the likelihood of radical resection, NAC appears to be better tolerated compared with adjuvant treatment [6]. Although limited by tissue heterogeneity, a hallmark of GC response to NAC provides an insight into tumor chemosensitivity [86,87]. The transition of recent findings in molecular biology into efficient therapeutic solutions remains one of the greatest challenges in the multimodal treatment of GC patients [4]. For example, results of the ToGA trial incorporated into clinical practice trastuzumab, a monoclonal antibody targeting Human Epidermal Receptor (HER2) over a decade ago [88]. The addition of trastuzumab to platinum-based doublet first-line palliative chemotherapy in GC patients with HER2 overexpression was associated with a decrease in the risk of death by 26%. Another milestone in the multimodal therapy of GC was established along with the results of the FLOT4-AIO trial, incorporating a docetaxel-based regimen as the perioperative treatment of choice for medically fit patients [89]. However, the impact of taxanes has been debated due to potential toxicity and uncertain clinical benefits in the geriatric population [30,89].
Recently, the results of the GASTFOX-PRODIGE 51 trial [90] were presented at the ESMO 2023 Congress. The study’s objective was to verify the benefit of integrating docetaxel into FOLFOX (modified FLOT = TFOT) in previously untreated advanced GC patients. In the TFOT group, an improved OS (HR = 0.82, 95% CI 0.68–0.99), PFS (median: 7.59 vs. 5.98, p = 0.007), and objective response rate (ORR, 66.2% vs. 57.5%, p = 0.04) were observed compared with a control group receiving FOLFOX. These findings further strengthen the significance of incorporating docetaxel into first-line chemotherapeutic regimens in advanced stages of GC.
However, up to 10% of locally advanced GC tumors present high MSI and programmed death-ligand 1 (PD-L1) expression, being the potential candidate for perioperative immune-checkpoint inhibitors (ICI) therapy. In the third interim analysis of the KEYNOTE-585 trial, the addition of pembrolizumab to chemotherapy demonstrated an increase in pathologic complete response (12.9% vs. 2%; p < 0.0001) while concurrently showing a statistically insignificant improvement in event-free survival (EFS, median 44.4 months vs. 25.3 months; HR 0.81; 95% CI 0.67–0.99; p = 0.0198) [91]. In a similar design, the MATTERHORN trial randomized patients to receive perioperative FLOT with placebo or FLOT plus durvalumab (anti-PD-L1 antibody), revealing a higher pathologic complete response rate in the group treated with the addition of durvalumab [92]. The percentage of patients undergoing surgery and achieving R0 resection was comparable between the two groups. The investigation is currently ongoing, focusing on the primary endpoint of EFS. It is crucial to highlight that patients included in these studies were biomarker unselected, therefore the survival benefit of perioperative immunotherapy is uncertain.
One of the main limitations of systemic chemotherapy is restricted penetration into the peritoneum, the most frequent location of metastatic disease and site of recurrence. The peritoneal dissemination may be diagnosed even in 40% of cases, most frequently during diagnostic laparoscopy, and reduce the median survival from 14 to 4 months [93,94]. The revolution in the treatment of peritoneal metastases was introduced by Paul Sugarbaker in 1989, proposing the Hyperthermic IntraPeritoneal Chemotherapy (HIPEC) method [95]. Despite evidence suggesting its effectiveness, the lack of high-quality evidence from randomized controlled trials restricts the widespread adoption of this therapy in GC patients, confining it to experimental settings only [96]. Among prophylactic, palliative, and pre- and postoperative indications for HIPEC, a group of patients undergoing NAC at high risk of peritoneal dissemination require special consideration, given the potential challenges in achieving curative-intent surgery. The therapeutic value of adjuvant HIPEC in patients with peritoneal metastases after NAC was suggested by the GASTRICHIP trial results [97]. The interim safety analysis confirmed that intraperitoneal perfusion of oxaliplatin with concurrent intravenous 5-FU administration results in equal morbidity when compared to cytoreductive surgery alone [98]. Although current data have not impacted actual state-of-the-art, results of the PERISCOPE II trial comparing standard-of-care systemic chemotherapy versus HIPEC [99] and the PREVENT trial assessing prophylactic use of HIPEC along with FLOT chemotherapy are anticipated [100].
Although identifying and mitigating risk factors for preoperative chemotherapy compliance and effectiveness is critical for improving outcomes of treatment, the proposed methodology for TNO implantation has certain limitations. First, while the TNO embraces various aspects of GC management, it may suffer from a lack of specificity regarding the methodology employed for data collection and analysis. Additionally, some rationales for TNO components such as time to surgery or nutrition rely on retrospective data, as there is no clear consensus or guidelines recommendations. Furthermore, the discussion on numerous evolving paradigms in GC treatment is provided, although without assessing the impact of these advancements on the proposed composite measure. However, it is important to note that the proposed version of TNO was developed through multi-institutional expert discussions, indicating a collaborative effort to address these limitations. Additionally, TNO will be further evaluated in prospective settings, which is crucial for validating its effectiveness and reliability in assessing outcomes of GC patients undergoing neoadjuvant therapy.

9. Conclusions

Despite the recent advancements in GC management and ongoing exploration of preoperative therapy, further investigations should help to establish outcomes assessment of current clinical pathways. A key strength of this narrative review is the demonstrated feasibility and the provided research background supporting the implementation of the first and novel composite measure representing the “ideal” and holistic care among patients with locally advanced GEJ and GC in the preoperative period. TNO might be useful for identifying and addressing specific areas of improvement, specifically chemotherapy compliance, to enhance the overall quality of care delivered to GC patients undergoing curatively-intended multimodal treatment. Further, in the ongoing discourse on the reevaluation of TO in GC surgery [19], we anticipate an evolution of the TNO scoring system due to continuous preoperative therapy investigations [9,101]. Moreover, it is necessary to conduct further analysis that will correlate clinical outcomes with the prognostic factors evaluated within the TNO framework.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/cancers16091721/s1. Figure S1: Flow chart of study path.

Author Contributions

Conceptualization—K.R.-P., Z.P., K.S., M.S., M.L., K.M., K.C., A.K., T.C. and J.C.; Data curation—Z.P., K.R.-P., M.L., K.M., K.C., A.K., B.P.L.W., J.W.V.S., I.G., G.P., C.E., M.B., G.D.M., G.L.B., P.M., R.R., U.F.R., A.D., S.S.G., Y.E., T.M.P., F.R., C.B. and W.P.P.; Formal Analysis—Z.P., K.R.-P., M.L., K.C., K.M., A.K., B.P.L.W., J.W.V.S., I.G., G.P., C.E., M.B., G.D.M., G.L.B., P.M., R.R., U.F.R., A.D., S.S.G., Y.E., T.M.P., F.R., C.B. and W.P.P.; Investigation—K.R.-P., Z.P., K.S., M.S., M.L., K.M., K.C., A.K., T.C., J.C., A.K., B.P.L.W., J.W.V.S., I.G., G.P., C.E., M.B., G.D.M., G.L.B., P.M., R.R., U.F.R., A.D., S.S.G., Y.E., T.M.P., F.R., C.B. and W.P.P.; Methodology—K.R.-P., Z.P., K.S., M.S., M.L., K.M., K.C., A.K., T.C., J.C., A.K., B.P.L.W., J.W.V.S., I.G., G.P., C.E., M.B., G.D.M., G.L.B., P.M., R.R., U.F.R., A.D., S.S.G., Y.E., T.M.P., F.R., C.B. and W.P.P.; Project administration—Z.P., K.R.-P., M.S., A.K., T.C., M.L., K.M., K.C., J.C., A.K., B.P.L.W., J.W.V.S., I.G., G.P., C.E., M.B., G.D.M., G.L.B., P.M., R.R., U.F.R., A.D., S.S.G., Y.E., T.M.P., F.R., C.B. and W.P.P.; Resources—Z.P. and K.R.-P.; Software—Z.P. and K.R.-P.; Supervision—B.P.L.W., J.W.V.S., I.G., G.P., C.E., M.B., G.D.M., G.L.B., P.M., R.R., U.F.R., A.D., S.S.G., Y.E., T.M.P., F.R., C.B. and W.P.P.; Validation—K.R.-P.; Visualization—Z.P. and K.R.-P.; Writing—original draft—Z.P. and K.R.-P.; Writing—review & editing—K.S., M.S., K.M.,K.C., M.L., A.K., T.C., J.C., A.K., B.P.L.W., J.W.V.S., I.G., G.P., C.E., M.B., G.D.M., G.L.B., P.M., R.R., U.F.R., A.D., S.S.G., Y.E., T.M.P., F.R., C.B. and W.P.P. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Acknowledgments

Authors would like to sincerely thank Brian Badgwell from the Department of Surgical Oncology, The University of Texas MD Anderson Cancer Center, for consulting Textbook Neoadjuvant Outcome idea and components.

Conflicts of Interest

The authors declare no conflicts of interest.

References

  1. Arnold, M.; Abnet, C.C.; Neale, R.E.; Vignat, J.; Giovannucci, E.L.; McGlynn, K.A.; Bray, F. Global Burden of 5 Major Types of Gastrointestinal Cancer. Gastroenterology 2020, 159, 335–349.e15. [Google Scholar] [CrossRef] [PubMed] [PubMed Central]
  2. Ferlay, J.E.M.; Lam, F. Global Cancer Observatory: Cancer Tomorrow; International Agency for Research on Cancer: Lyon, France, 2018; Available online: https://gco.iarc.fr/tomorrow/en (accessed on 2 February 2024).
  3. Aquina, C.T.; Ejaz, A.; Tsung, A.; Pawlik, T.M.; Cloyd, J.M. National Trends in the Use of Neoadjuvant Therapy before Cancer Surgery in the US from 2004 to 2016. JAMA Netw. Open 2021, 4, e211031. [Google Scholar] [CrossRef] [PubMed] [PubMed Central]
  4. Smyth, E.C.; Nilsson, M.; Grabsch, H.I.; van Grieken, N.C.; Lordick, F. Gastric cancer. Lancet 2020, 396, 635–648. [Google Scholar] [CrossRef] [PubMed]
  5. Cunningham, D.; Allum, W.H.; Stenning, S.P.; Thompson, J.N.; Van de Velde, C.J.H.; Nicolson, M.; Scarffe, J.H.; Lofts, F.J.; Falk, S.J.; Iveson, T.J.; et al. Perioperative Chemotherapy versus Surgery Alone for Resectable Gastroesophageal Cancer. N. Engl. J. Med. 2006, 355, 11–20. [Google Scholar] [CrossRef] [PubMed]
  6. Al-Batran, S.E.; Hofheinz, R.D.; Pauligk, C.; Kopp, H.G.; Haag, G.M.; Luley, K.B.; Meiler, J.; Homann, N.; Lorenzen, S.; Schmalenberg, H.; et al. Histopathological regression after neoadjuvant docetaxel, oxaliplatin, fluorouracil, and leucovorin versus epirubicin, cisplatin, and fluorouracil or capecitabine in patients with resectable gastric or gastro-oesophageal junction adenocarcinoma (FLOT4-AIO): Results from the phase 2 part of a multicentre, open-label, randomised phase 2/3 trial. Lancet Oncol. 2016, 17, 1697–1708. [Google Scholar] [CrossRef] [PubMed]
  7. Lee, J.; Lim, D.H.; Kim, S.; Park, S.H.; Park, J.O.; Park, Y.S.; Lim, H.Y.; Choi, M.G.; Sohn, T.S.; Noh, J.H.; et al. Phase III trial comparing capecitabine plus cisplatin versus capecitabine plus cisplatin with concurrent capecitabine radiotherapy in completely resected gastric cancer with D2 lymph node dissection: The ARTIST trial. J. Clin. Oncol. 2012, 30, 268–273. [Google Scholar] [CrossRef] [PubMed]
  8. Park, S.H.; Zang, D.Y.; Han, B.; Ji, J.H.; Kim, T.G.; Oh, S.Y.; Hwang, I.G.; Kim, J.H.; Shin, D.; Lim, D.H.; et al. ARTIST 2: Interim results of a phase III trial involving adjuvant chemotherapy and/or chemoradiotherapy after D2-gastrectomy in stage II/III gastric cancer (GC). J. Clin. Oncol. 2019, 37, 4001. [Google Scholar] [CrossRef]
  9. Leong, T.; Smithers, B.M.; Michael, M.; Gebski, V.; Boussioutas, A.; Miller, D.; Simes, J.; Zalcberg, J.; Haustermans, K.; Lordick, F.; et al. TOPGEAR: A randomised phase III trial of perioperative ECF chemotherapy versus preoperative chemoradiation plus perioperative ECF chemotherapy for resectable gastric cancer (an international, intergroup trial of the AGITG/TROG/EORTC/NCIC CTG). BMC Cancer 2015, 15, 532. [Google Scholar] [CrossRef] [PubMed]
  10. Donlon, N.E.; Moran, B.; Kamilli, A.; Davern, M.; Sheppard, A.; King, S.; Donohoe, C.L.; Lowery, M.; Cunningham, M.; Ravi, N.; et al. CROSS Versus FLOT Regimens in Esophageal and Esophagogastric Junction Adenocarcinoma: A Propensity-Matched Comparison. Ann. Surg. 2022, 276, 792–798. [Google Scholar] [CrossRef] [PubMed]
  11. Reynolds, J.V.; Preston, S.R.; O’Neill, B.; Lowery, M.A.; Baeksgaard, L.; Crosby, T.; Cunningham, M.; Cuffe, S.; Griffiths, G.O.; Parker, I.; et al. Trimodality therapy versus perioperative chemotherapy in the management of locally advanced adenocarcinoma of the oesophagus and oesophagogastric junction (Neo-AEGIS): An open-label, randomised, phase 3 trial. Lancet Gastroenterol. Hepatol. 2023, 8, 1015–1027. [Google Scholar] [CrossRef] [PubMed] [PubMed Central]
  12. Hoeppner, J.; Lordick, F.; Brunner, T.; Glatz, T.; Bronsert, P.; Rothling, N.; Schmoor, C.; Lorenz, D.; Ell, C.; Hopt, U.T.; et al. ESOPEC: Prospective randomized controlled multicenter phase III trial comparing perioperative chemotherapy (FLOT protocol) to neoadjuvant chemoradiation (CROSS protocol) in patients with adenocarcinoma of the esophagus (NCT02509286). BMC Cancer 2016, 16, 503. [Google Scholar] [CrossRef] [PubMed] [PubMed Central]
  13. Chiche, L.; Yang, H.K.; Abbassi, F.; Robles-Campos, R.; Stain, S.C.; Ko, C.Y.; Neumayer, L.A.; Pawlik, T.M.; Barkun, J.S.; Clavien, P.A. Quality and Outcome Assessment for Surgery. Ann. Surg. 2023, 278, 647–654. [Google Scholar] [CrossRef] [PubMed]
  14. Ajani, J.A.; D’Amico, T.A.; Bentrem, D.J.; Chao, J.; Cooke, D.; Corvera, C.; Das, P.; Enzinger, P.C.; Enzler, T.; Fanta, P.; et al. Gastric Cancer, Version 2.2022, NCCN Clinical Practice Guidelines in Oncology. J. Natl. Compr. Cancer Netw. 2023, 20, 167–192. [Google Scholar] [CrossRef] [PubMed]
  15. Shannon, A.B.; Straker, R.J., 3rd; Keele, L.; Fraker, D.L.; Roses, R.E.; Miura, J.T.; Karakousis, G.C. Lymph Node Evaluation after Neoadjuvant Chemotherapy for Patients with Gastric Cancer. Ann. Surg. Oncol. 2022, 29, 1242–1253. [Google Scholar] [CrossRef] [PubMed]
  16. Kong, S.H.; Lee, H.J.; Ahn, H.S.; Kim, J.W.; Kim, W.H.; Lee, K.U.; Yang, H.K. Stage migration effect on survival in gastric cancer surgery with extended lymphadenectomy: The reappraisal of positive lymph node ratio as a proper N-staging. Ann. Surg. 2012, 255, 50–58. [Google Scholar] [CrossRef] [PubMed]
  17. Smith, D.D.; Schwarz, R.R.; Schwarz, R.E. Impact of total lymph node count on staging and survival after gastrectomy for gastric cancer: Data from a large US-population database. J. Clin. Oncol. 2005, 23, 7114–7124. [Google Scholar] [CrossRef] [PubMed]
  18. Baxter, N.N.; Tuttle, T.M. Inadequacy of lymph node staging in gastric cancer patients: A population-based study. Ann. Surg. Oncol. 2005, 12, 981–987. [Google Scholar] [CrossRef] [PubMed]
  19. Carbonell-Morote, S.; Yang, H.K.; Lacueva, J.; Rubio-Garcia, J.J.; Alacan-Friedrich, L.; Fierley, L.; Villodre, C.; Ramia, J.M. Textbook outcome in oncological gastric surgery: A systematic review and call for an international consensus. World J. Surg. Oncol. 2023, 21, 288. [Google Scholar] [CrossRef] [PubMed] [PubMed Central]
  20. O’Brien, S.M.; Shahian, D.M.; DeLong, E.R.; Normand, S.L.; Edwards, F.H.; Ferraris, V.A.; Haan, C.K.; Rich, J.B.; Shewan, C.M.; Dokholyan, R.S.; et al. Quality measurement in adult cardiac surgery: Part 2—Statistical considerations in composite measure scoring and provider rating. Ann. Thorac. Surg. 2007, 83, S13–S26. [Google Scholar] [CrossRef] [PubMed]
  21. van der Kaaij, R.T.; de Rooij, M.V.; van Coevorden, F.; Voncken, F.E.M.; Snaebjornsson, P.; Boot, H.; van Sandick, J.W. Using textbook outcome as a measure of quality of care in oesophagogastric cancer surgery. Br. J. Surg. 2018, 105, 561–569. [Google Scholar] [CrossRef] [PubMed]
  22. Merath, K.; Chen, Q.; Bagante, F.; Alexandrescu, S.; Marques, H.P.; Aldrighetti, L.; Maithel, S.K.; Pulitano, C.; Weiss, M.J.; Bauer, T.W.; et al. A Multi-institutional International Analysis of Textbook Outcomes among Patients Undergoing Curative-Intent Resection of Intrahepatic Cholangiocarcinoma. JAMA Surg. 2019, 154, e190571. [Google Scholar] [CrossRef] [PubMed] [PubMed Central]
  23. Sedlak, K.; Rawicz-Pruszynski, K.; Mlak, R.; Van Sandick, J.; Gisbertz, S.; Pera, M.; Dal Cero, M.; Baiocchi, G.L.; Celotti, A.; Morgagni, P.; et al. Textbook Oncological Outcome in European Gastrodata. Ann. Surg. 2023, 278, 823–831. [Google Scholar] [CrossRef] [PubMed]
  24. Basch, E.; Deal, A.M.; Kris, M.G.; Scher, H.I.; Hudis, C.A.; Sabbatini, P.; Rogak, L.; Bennett, A.V.; Dueck, A.C.; Atkinson, T.M.; et al. Symptom Monitoring with Patient-Reported Outcomes during Routine Cancer Treatment: A Randomized Controlled Trial. J. Clin. Oncol. 2016, 34, 557–565. [Google Scholar] [CrossRef] [PubMed] [PubMed Central]
  25. Basch, E.; Deal, A.M.; Dueck, A.C.; Scher, H.I.; Kris, M.G.; Hudis, C.; Schrag, D. Overall Survival Results of a Trial Assessing Patient-Reported Outcomes for Symptom Monitoring during Routine Cancer Treatment. JAMA 2017, 318, 197–198. [Google Scholar] [CrossRef] [PubMed] [PubMed Central]
  26. Kim, T.H.; Kim, I.H.; Kang, S.J.; Choi, M.; Kim, B.H.; Eom, B.W.; Kim, B.J.; Min, B.H.; Choi, C.I.; Shin, C.M.; et al. Korean Practice Guidelines for Gastric Cancer 2022: An Evidence-based, Multidisciplinary Approach. J. Gastric Cancer 2023, 23, 3–106. [Google Scholar] [CrossRef] [PubMed] [PubMed Central]
  27. Claassen, Y.H.M.; Hartgrink, H.H.; Dikken, J.L.; de Steur, W.O.; van Sandick, J.W.; van Grieken, N.C.T.; Cats, A.; Trip, A.K.; Jansen, E.P.M.; Meershoek-Klein Kranenbarg, W.M.; et al. Surgical morbidity and mortality after neoadjuvant chemotherapy in the CRITICS gastric cancer trial. Eur. J. Surg. Oncol. 2018, 44, 613–619. [Google Scholar] [CrossRef] [PubMed]
  28. Wu, C.; Wang, N.; Zhou, H.; Wang, T.; Mao, Q.; Zhang, X.; Zhao, D. Effects of Neoadjuvant Chemotherapy Toxicity and Postoperative Complications on Short-term and Long-term Outcomes After Curative Resection of Gastric Cancer. J. Gastrointest. Surg. 2020, 24, 1278–1289. [Google Scholar] [CrossRef] [PubMed]
  29. Coccolini, F.; Nardi, M.; Montori, G.; Ceresoli, M.; Celotti, A.; Cascinu, S.; Fugazzola, P.; Tomasoni, M.; Glehen, O.; Catena, F.; et al. Neoadjuvant chemotherapy in advanced gastric and esophago-gastric cancer. Meta-analysis of randomized trials. Int. J. Surg. 2018, 51, 120–127. [Google Scholar] [CrossRef] [PubMed]
  30. Lordick, F.; Carneiro, F.; Cascinu, S.; Fleitas, T.; Haustermans, K.; Piessen, G.; Vogel, A.; Smyth, E.C.; on behalf of the ESMO Guidelines Committee. Gastric cancer: ESMO Clinical Practice Guideline for diagnosis, treatment and follow-up. Ann. Oncol. 2022, 33, 1005–1020. [Google Scholar] [CrossRef] [PubMed]
  31. Services Usdohah. Common Terminology Criteria for Adverse Events (CTCAE) Version 5.0; Services Usdohah: Beijing, China, 2017. [Google Scholar]
  32. Ruol, A.; Portale, G.; Castoro, C.; Merigliano, S.; Cagol, M.; Cavallin, F.; Chiarion Sileni, V.; Corti, L.; Rampado, S.; Costantini, M.; et al. Effects of neoadjuvant therapy on perioperative morbidity in elderly patients undergoing esophagectomy for esophageal cancer. Ann. Surg. Oncol. 2007, 14, 3243–3250. [Google Scholar] [CrossRef] [PubMed]
  33. Kudou, K.; Nakashima, Y.; Haruta, Y.; Nambara, S.; Tsuda, Y.; Kusumoto, E.; Ando, K.; Kimura, Y.; Hashimoto, K.; Yoshinaga, K.; et al. Comparison of Inflammation-Based Prognostic Scores Associated with the Prognostic Impact of Adenocarcinoma of Esophagogastric Junction and Upper Gastric Cancer. Ann. Surg. Oncol. 2021, 28, 2059–2067. [Google Scholar] [CrossRef] [PubMed]
  34. Hanahan, D.; Weinberg, R.A. Hallmarks of cancer: The next generation. Cell 2011, 144, 646–674. [Google Scholar] [CrossRef] [PubMed]
  35. Grenader, T.; Waddell, T.; Peckitt, C.; Oates, J.; Starling, N.; Cunningham, D.; Bridgewater, J. Prognostic value of neutrophil-to-lymphocyte ratio in advanced oesophago-gastric cancer: Exploratory analysis of the REAL-2 trial. Ann. Oncol. 2016, 27, 687–692. [Google Scholar] [CrossRef] [PubMed]
  36. Skorzewska, M.; Pikula, A.; Geca, K.; Mlak, R.; Rawicz-Pruszynski, K.; Sedlak, K.; Pasnik, I.; Polkowski, W.P. Systemic inflammatory response markers for prediction of response to neoadjuvant chemotherapy in patients with advanced gastric cancer. Cytokine 2023, 172, 156389. [Google Scholar] [CrossRef] [PubMed]
  37. Jiang, X.; Hiki, N.; Nunobe, S.; Kumagai, K.; Kubota, T.; Aikou, S.; Sano, T.; Yamaguchi, T. Prognostic importance of the inflammation-based Glasgow prognostic score in patients with gastric cancer. Br. J. Cancer 2012, 107, 275–279. [Google Scholar] [CrossRef] [PubMed] [PubMed Central]
  38. Nakamura, N.; Kinami, S.; Tomita, Y.; Miyata, T.; Fujita, H.; Takamura, H.; Ueda, N.; Kosaka, T. The neutrophil/lymphocyte ratio as a predictor of successful conversion surgery for stage IV gastric cancer: A retrospective study. BMC Cancer 2020, 20, 363. [Google Scholar] [CrossRef] [PubMed] [PubMed Central]
  39. Pikula, A.; Skorzewska, M.; Pelc, Z.; Mlak, R.; Geca, K.; Sedlak, K.; Cisel, B.; Kwietniewska, M.; Rawicz-Pruszynski, K.; Polkowski, W.P. Prognostic Value of Systemic Inflammatory Response Markers in Patients Undergoing Neoadjuvant Chemotherapy and Gastrectomy for Advanced Gastric Cancer in the Eastern European Population. Cancers 2022, 14, 1997. [Google Scholar] [CrossRef] [PubMed] [PubMed Central]
  40. Grenader, T.; Plotkin, Y.; Mohammadi, B.; Dawas, K.; Hashemi, M.; Mughal, M.; Bridgewater, J.A. Predictive Value of the Neutrophil/Lymphocyte Ratio in Peritoneal and/or Metastatic Disease at Staging Laparoscopy for Gastric and Esophageal Adenocarcinoma. J. Gastrointest. Cancer 2015, 46, 267–271. [Google Scholar] [CrossRef] [PubMed]
  41. Miyamoto, R.; Inagawa, S.; Sano, N.; Tadano, S.; Adachi, S.; Yamamoto, M. The neutrophil-to-lymphocyte ratio (NLR) predicts short-term and long-term outcomes in gastric cancer patients. Eur. J. Surg. Oncol. 2018, 44, 607–612. [Google Scholar] [CrossRef] [PubMed]
  42. Xu, Z.; Xu, W.; Cheng, H.; Shen, W.; Ying, J.; Cheng, F.; Xu, W. The Prognostic Role of the Platelet-Lymphocytes Ratio in Gastric Cancer: A Meta-Analysis. PLoS ONE 2016, 11, e0163719. [Google Scholar] [CrossRef] [PubMed] [PubMed Central]
  43. Xie, H.; Ruan, G.; Ge, Y.; Zhang, Q.; Zhang, H.; Lin, S.; Song, M.; Zhang, X.; Liu, X.; Li, X.; et al. Inflammatory burden as a prognostic biomarker for cancer. Clin. Nutr. 2022, 41, 1236–1243. [Google Scholar] [CrossRef] [PubMed]
  44. Sato, Y.; Okamoto, K.; Kawaguchi, T.; Nakamura, F.; Miyamoto, H.; Takayama, T. Treatment Response Predictors of Neoadjuvant Therapy for Locally Advanced Gastric Cancer: Current Status and Future Perspectives. Biomedicines 2022, 10, 1614. [Google Scholar] [CrossRef] [PubMed] [PubMed Central]
  45. Lin, J.X.; Wang, Z.K.; Huang, Y.Q.; Xie, J.W.; Wang, J.B.; Lu, J.; Chen, Q.Y.; Lin, M.; Tu, R.H.; Huang, Z.N.; et al. Dynamic Changes in Pre-and Postoperative Levels of Inflammatory Markers and Their Effects on the Prognosis of Patients with Gastric Cancer. J. Gastrointest. Surg. 2021, 25, 387–396. [Google Scholar] [CrossRef] [PubMed] [PubMed Central]
  46. Ding, P.; Wu, H.; Liu, P.; Sun, C.; Yang, P.; Tian, Y.; Guo, H.; Liu, Y.; Zhao, Q. The inflammatory burden index: Apromising prognostic predictor in patients with locally advanced gastric cancer. Clin. Nutr. 2023, 42, 247–248. [Google Scholar] [CrossRef] [PubMed]
  47. Fournier, L.; de Geus-Oei, L.F.; Regge, D.; Oprea-Lager, D.E.; D’Anastasi, M.; Bidaut, L.; Bauerle, T.; Lopci, E.; Cappello, G.; Lecouvet, F.; et al. Twenty Years on: RECIST as a Biomarker of Response in Solid Tumours an EORTC Imaging Group—ESOI Joint Paper. Front. Oncol. 2021, 11, 800547. [Google Scholar] [CrossRef] [PubMed] [PubMed Central]
  48. Japanese Gastric Cancer Association. Japanese Gastric Cancer Treatment Guidelines 2021 (6th edition). Gastric Cancer 2023, 26, 1–25. [Google Scholar] [CrossRef] [PubMed] [PubMed Central]
  49. Schwartz, L.H.; Seymour, L.; Litiere, S.; Ford, R.; Gwyther, S.; Mandrekar, S.; Shankar, L.; Bogaerts, J.; Chen, A.; Dancey, J.; et al. RECIST 1.1—Standardisation and disease-specific adaptations: Perspectives from the RECIST Working Group. Eur. J. Cancer 2016, 62, 138–145. [Google Scholar] [CrossRef] [PubMed] [PubMed Central]
  50. Eisenhauer, E.A.; Therasse, P.; Bogaerts, J.; Schwartz, L.H.; Sargent, D.; Ford, R.; Dancey, J.; Arbuck, S.; Gwyther, S.; Mooney, M.; et al. New response evaluation criteria in solid tumours: Revised RECIST guideline (version 1.1). Eur. J. Cancer 2009, 45, 228–247. [Google Scholar] [CrossRef] [PubMed]
  51. Goebel, J.; Hoischen, J.; Gramsch, C.; Schemuth, H.P.; Hoffmann, A.C.; Umutlu, L.; Nassenstein, K. Tumor response assessment: Comparison between unstructured free text reporting in routine clinical workflow and computer-aided evaluation based on RECIST 1.1 criteria. J. Cancer Res. Clin. Oncol. 2017, 143, 2527–2533. [Google Scholar] [CrossRef] [PubMed]
  52. Pelc, Z.; Skorzewska, M.; Rawicz-Pruszynski, K.; Polkowski, W.P. Lymph Node Involvement in Advanced Gastric Cancer in the Era of Multimodal Treatment-Oncological and Surgical Perspective. Cancers 2021, 13, 2509. [Google Scholar] [CrossRef] [PubMed] [PubMed Central]
  53. Bi, W.L.; Hosny, A.; Schabath, M.B.; Giger, M.L.; Birkbak, N.J.; Mehrtash, A.; Allison, T.; Arnaout, O.; Abbosh, C.; Dunn, I.F.; et al. Artificial intelligence in cancer imaging: Clinical challenges and applications. CA Cancer J. Clin. 2019, 69, 127–157. [Google Scholar] [CrossRef] [PubMed] [PubMed Central]
  54. Berbis, M.A.; Aneiros-Fernandez, J.; Mendoza Olivares, F.J.; Nava, E.; Luna, A. Role of artificial intelligence in multidisciplinary imaging diagnosis of gastrointestinal diseases. World J. Gastroenterol. 2021, 27, 4395–4412. [Google Scholar] [CrossRef] [PubMed] [PubMed Central]
  55. Rawicz-Pruszynski, K.; Erodotou, M.; Pelc, Z.; Sedlak, K.; Polkowski, W.; Pawlik, T.M.; Wijnhoven, B.P.L. Techniques of staging laparoscopy and peritoneal fluid assessment in gastric cancer: A systematic review. Int. J. Surg. 2023, 109, 3578–3589. [Google Scholar] [CrossRef] [PubMed] [PubMed Central]
  56. Ikoma, N.; Blum, M.; Chiang, Y.J.; Estrella, J.S.; Roy-Chowdhuri, S.; Fournier, K.; Mansfield, P.; Ajani, J.A.; Badgwell, B.D. Yield of Staging Laparoscopy and Lavage Cytology for Radiologically Occult Peritoneal Carcinomatosis of Gastric Cancer. Ann. Surg. Oncol. 2016, 23, 4332–4337. [Google Scholar] [CrossRef] [PubMed]
  57. Rawicz-Pruszynski, K.; Mielko, J.; Pudlo, K.; Lisiecki, R.; Skoczylas, T.; Murawa, D.; Polkowski, W.P. Yield of staging laparoscopy in gastric cancer is influenced by Lauren histologic subtype. J. Surg. Oncol. 2019, 120, 1148–1153. [Google Scholar] [CrossRef] [PubMed]
  58. Sando, A.D.; Fougner, R.; Royset, E.S.; Dai, H.Y.; Gronbech, J.E.; Bringeland, E.A. Response Evaluation after Neoadjuvant Chemotherapy for Resectable Gastric Cancer. Cancers 2023, 15, 2318. [Google Scholar] [CrossRef] [PubMed] [PubMed Central]
  59. Pressoir, M.; Desne, S.; Berchery, D.; Rossignol, G.; Poiree, B.; Meslier, M.; Traversier, S.; Vittot, M.; Simon, M.; Gekiere, J.P.; et al. Prevalence, risk factors and clinical implications of malnutrition in French Comprehensive Cancer Centres. Br. J. Cancer 2010, 102, 966–971. [Google Scholar] [CrossRef] [PubMed] [PubMed Central]
  60. Attar, A.; Malka, D.; Sabate, J.M.; Bonnetain, F.; Lecomte, T.; Aparicio, T.; Locher, C.; Laharie, D.; Ezenfis, J.; Taieb, J. Malnutrition is high and underestimated during chemotherapy in gastrointestinal cancer: An AGEO prospective cross-sectional multicenter study. Nutr. Cancer 2012, 64, 535–542. [Google Scholar] [CrossRef] [PubMed]
  61. Schiessel, D.L.; Orrutea, A.K.G.; Tramontt, C.; Cavagnari, M.A.V.; Novello, D.; Macedo, D.S. Clinical and nutritional characteristics on overall survival impact in patients with gastrointestinal cancer. Clin Nutr. ESPEN 2022, 48, 336–341. [Google Scholar] [CrossRef] [PubMed]
  62. Cederholm, T.; Barazzoni, R.; Austin, P.; Ballmer, P.; Biolo, G.; Bischoff, S.C.; Compher, C.; Correia, I.; Higashiguchi, T.; Holst, M.; et al. ESPEN guidelines on definitions and terminology of clinical nutrition. Clin. Nutr. 2017, 36, 49–64. [Google Scholar] [CrossRef] [PubMed]
  63. Gioulbasanis, I.; Martin, L.; Baracos, V.E.; Thezenas, S.; Koinis, F.; Senesse, P. Nutritional assessment in overweight and obese patients with metastatic cancer: Does it make sense? Ann. Oncol. 2015, 26, 217–221. [Google Scholar] [CrossRef] [PubMed]
  64. Cederholm, T.; Bosaeus, I.; Barazzoni, R.; Bauer, J.; Van Gossum, A.; Klek, S.; Muscaritoli, M.; Nyulasi, I.; Ockenga, J.; Schneider, S.M.; et al. Diagnostic criteria for malnutrition—An ESPEN Consensus Statement. Clin. Nutr. 2015, 34, 335–340. [Google Scholar] [CrossRef] [PubMed]
  65. Flegal, K.M.; Kit, B.K.; Orpana, H.; Graubard, B.I. Association of all-cause mortality with overweight and obesity using standard body mass index categories: A systematic review and meta-analysis. JAMA 2013, 309, 71–82. [Google Scholar] [CrossRef] [PubMed] [PubMed Central]
  66. Solanki, S.; Chakinala, R.C.; Haq, K.F.; Khan, M.A.; Kifayat, A.; Linder, K.; Khan, Z.; Mansuri, U.; Haq, K.S.; Nabors, C.; et al. Inpatient burden of gastric cancer in the United States. Ann. Transl. Med. 2019, 7, 772. [Google Scholar] [CrossRef] [PubMed] [PubMed Central]
  67. Ida, S.; Kumagai, K.; Nunobe, S. Current status of perioperative nutritional intervention and exercise in gastric cancer surgery: A review. Ann. Gastroenterol. Surg. 2022, 6, 197–203. [Google Scholar] [CrossRef] [PubMed] [PubMed Central]
  68. Kovoor, J.G.; Nann, S.D.; Barot, D.D.; Garg, D.; Hains, L.; Stretton, B.; Ovenden, C.D.; Bacchi, S.; Chan, E.; Gupta, A.K.; et al. Prehabilitation for general surgery: A systematic review of randomized controlled trials. ANZ J. Surg. 2023, 93, 2411–2425. [Google Scholar] [CrossRef] [PubMed]
  69. Tsoulfas, G. The Critical Evolution of the Concept of Frailty in Surgery. Ann. Surg. Oncol. 2024, 31, 10–11. [Google Scholar] [CrossRef] [PubMed]
  70. Lee, D.U.; Kwon, J.; Han, J.; Fan, G.H.; Hastie, D.J.; Lee, K.J.; Karagozian, R. The clinical impact of frailty on the postoperative outcomes of patients undergoing gastrectomy for gastric cancer: A propensity-score matched database study. Gastric Cancer 2022, 25, 450–458. [Google Scholar] [CrossRef] [PubMed]
  71. Arya, S.; Varley, P.; Youk, A.; Borrebach, J.D.; Perez, S.; Massarweh, N.N.; Johanning, J.M.; Hall, D.E. Recalibration and External Validation of the Risk Analysis Index: A Surgical Frailty Assessment Tool. Ann. Surg. 2020, 272, 996–1005. [Google Scholar] [CrossRef] [PubMed] [PubMed Central]
  72. Ljungqvist, O.; Scott, M.; Fearon, K.C. Enhanced Recovery after Surgery: A Review. JAMA Surg. 2017, 152, 292–298. [Google Scholar] [CrossRef] [PubMed]
  73. Gustafsson, U.O.; Oppelstrup, H.; Thorell, A.; Nygren, J.; Ljungqvist, O. Adherence to the ERAS protocol is Associated with 5-Year Survival after Colorectal Cancer Surgery: A Retrospective Cohort Study. World J. Surg. 2016, 40, 1741–1747. [Google Scholar] [CrossRef] [PubMed]
  74. Romario, U.F.; Ascari, F.; De Pascale, S.; GIRCG. Implementation of the ERAS program in gastric surgery: A nationwide survey in Italy. Updates Surg. 2023, 75, 141–148. [Google Scholar] [CrossRef] [PubMed] [PubMed Central]
  75. Vitaloni, M.; Caccialanza, R.; Ravasco, P.; Carrato, A.; Kapala, A.; de van der Schueren, M.; Constantinides, D.; Backman, E.; Chuter, D.; Santangelo, C.; et al. The impact of nutrition on the lives of patients with digestive cancers: A position paper. Support. Care Cancer 2022, 30, 7991–7996. [Google Scholar] [CrossRef] [PubMed] [PubMed Central]
  76. Caccialanza, R.; Goldwasser, F.; Marschal, O.; Ottery, F.; Schiefke, I.; Tilleul, P.; Zalcman, G.; Pedrazzoli, P. Unmet needs in clinical nutrition in oncology: A multinational analysis of real-world evidence. Ther. Adv. Med. Oncol. 2020, 12, 1758835919899852. [Google Scholar] [CrossRef] [PubMed] [PubMed Central]
  77. Team, Working Group I. The SuRF Report 2. In Surveillance of Chronic Disease Risk Factors: Country-Level Data and Comparable Estimates; WHO: Geneva, Switzerland, 2005; p. 22. [Google Scholar]
  78. Francois, Y.; Nemoz, C.J.; Baulieux, J.; Vignal, J.; Grandjean, J.P.; Partensky, C.; Souquet, J.C.; Adeleine, P.; Gerard, J.P. Influence of the interval between preoperative radiation therapy and surgery on downstaging and on the rate of sphincter-sparing surgery for rectal cancer: The Lyon R90-01 randomized trial. J. Clin. Oncol. 1999, 17, 2396. [Google Scholar] [CrossRef] [PubMed]
  79. Wolthuis, A.M.; Penninckx, F.; Haustermans, K.; De Hertogh, G.; Fieuws, S.; Van Cutsem, E.; D’Hoore, A. Impact of interval between neoadjuvant chemoradiotherapy and TME for locally advanced rectal cancer on pathologic response and oncologic outcome. Ann. Surg. Oncol. 2012, 19, 2833–2841. [Google Scholar] [CrossRef] [PubMed]
  80. Omarini, C.; Guaitoli, G.; Noventa, S.; Andreotti, A.; Gambini, A.; Palma, E.; Papi, S.; Tazzioli, G.; Balduzzi, S.; Dominici, M.; et al. Impact of time to surgery after neoadjuvant chemotherapy in operable breast cancer patients. Eur. J. Surg. Oncol. 2017, 43, 613–618. [Google Scholar] [CrossRef] [PubMed]
  81. Nilsson, K.; Klevebro, F.; Sunde, B.; Rouvelas, I.; Lindblad, M.; Szabo, E.; Halldestam, I.; Smedh, U.; Wallner, B.; Johansson, J.; et al. Oncological outcomes of standard versus prolonged time to surgery after neoadjuvant chemoradiotherapy for oesophageal cancer in the multicentre, randomised, controlled NeoRes II trial. Ann. Oncol. 2023, 34, 1015–1024. [Google Scholar] [CrossRef] [PubMed]
  82. Zhai, Y.; Zheng, Z.; Deng, W.; Yin, J.; Bai, Z.; Liu, X.; Zhang, J.; Zhang, Z. Interval time between neoadjuvant chemotherapy and surgery in advanced gastric cancer doesn’t affect outcome: A meta analysis. Front. Surg. 2022, 9, 1047456. [Google Scholar] [CrossRef] [PubMed] [PubMed Central]
  83. Liu, Z.; Zhang, Z.; Liu, H.; Chen, J. Time to surgery does not affect oncologic outcomes in locally advanced gastric cancer after neoadjuvant chemotherapy: A meta-analysis. Future Oncol. 2023, 19, 397–408. [Google Scholar] [CrossRef] [PubMed]
  84. Reinsoo, A.; Bausys, A.; Umarik, T.; Strupas, K. ASO Author Reflections: Gastrectomy within 30 Days after Neoadjuvant Chemotherapy is Associated with the Highest Rate of Major Pathologic Response in Advanced Gastric Cancer. Ann. Surg. Oncol. 2021, 28, 4456–4457. [Google Scholar] [CrossRef] [PubMed]
  85. Riascos, M.C.; Greenberg, J.A.; Palacardo, F.; Edelmuth, R.; Lewis, V.C.; An, A.; Najah, H.; Al Asadi, H.; Safe, P.; Finnerty, B.M.; et al. Timing to Surgery and Lymph Node Upstaging in Gastric Cancer: An NCDB Analysis. Ann. Surg. Oncol. 2023, 31, 1714–1724. [Google Scholar] [CrossRef] [PubMed]
  86. Grivennikov, S.I.; Greten, F.R.; Karin, M. Immunity, inflammation, and cancer. Cell 2010, 140, 883–899. [Google Scholar] [CrossRef] [PubMed] [PubMed Central]
  87. de Visser, K.E.; Jonkers, J. Towards understanding the role of cancer-associated inflammation in chemoresistance. Curr. Pharm. Des. 2009, 15, 1844–1853. [Google Scholar] [CrossRef] [PubMed]
  88. Bang, Y.J.; Van Cutsem, E.; Feyereislova, A.; Chung, H.C.; Shen, L.; Sawaki, A.; Lordick, F.; Ohtsu, A.; Omuro, Y.; Satoh, T.; et al. Trastuzumab in combination with chemotherapy versus chemotherapy alone for treatment of HER2-positive advanced gastric or gastro-oesophageal junction cancer (ToGA): A phase 3, open-label, randomised controlled trial. Lancet 2010, 376, 687–697. [Google Scholar] [CrossRef] [PubMed]
  89. Al-Batran, S.E.; Homann, N.; Pauligk, C.; Goetze, T.O.; Meiler, J.; Kasper, S.; Kopp, H.G.; Mayer, F.; Haag, G.M.; Luley, K.; et al. Perioperative chemotherapy with fluorouracil plus leucovorin, oxaliplatin, and docetaxel versus fluorouracil or capecitabine plus cisplatin and epirubicin for locally advanced, resectable gastric or gastro-oesophageal junction adenocarcinoma (FLOT4): A randomised, phase 2/3 trial. Lancet 2019, 393, 1948–1957. [Google Scholar] [CrossRef] [PubMed]
  90. Zaanan, A.; Bouche, O.; de la Fouchardiere, C.; Samalin-Scalzi, E.; Le Malicot, K.; Pernot, S.; Artru, P.; Ly Lebrun, V.; Aldabbagh, K.; Khemissa Akouz, F.; et al. LBA77 5-fluorouracil and oxaliplatin with or without docetaxel in the first-line treatment of HER2 negative locally advanced (LA) unresectable or metastatic gastric or gastro-esophageal junction (GEJ) adenocarcinoma (GASTFOX-PRODIGE 51): A randomized phase III trial sponsored by the FFCD. Ann. Oncol. 2023, 34, S1318. [Google Scholar] [CrossRef]
  91. Shitara, K.; Rha, S.Y.; Wyrwicz, L.S.; Oshima, T.; Karaseva, N.; Osipov, M.; Yasui, H.; Yabusaki, H.; Afanasyev, S.; Park, Y.-K.; et al. LBA74 Pembrolizumab plus chemotherapy vs chemotherapy as neoadjuvant and adjuvant therapy in locally-advanced gastric and gastroesophageal junction cancer: The phase 3 KEYNOTE-585 study. Ann. Oncol. 2023, 34, S1316. [Google Scholar] [CrossRef]
  92. Janjigian, Y.Y.; Al-Batran, S.-E.; Wainberg, Z.A.; Van Cutsem, E.; Molena, D.; Muro, K.; Hyung, W.J.; Wyrwicz, L.S.; Oh, D.-Y.; Omori, T.; et al. LBA73 Pathological complete response (pCR) to durvalumab plus 5-fluorouracil, leucovorin, oxaliplatin and docetaxel (FLOT) in resectable gastric and gastroesophageal junction cancer (GC/GEJC): Interim results of the global, phase 3 MATTERHORN study. Ann. Oncol. 2023, 34, S1315–S1316. [Google Scholar] [CrossRef]
  93. Rijken, A.; Lurvink, R.J.; Luyer, M.D.P.; Nieuwenhuijzen, G.A.P.; van Erning, F.N.; van Sandick, J.W.; de Hingh, I. The Burden of Peritoneal Metastases from Gastric Cancer: A Systematic Review on the Incidence, Risk Factors and Survival. J. Clin. Med. 2021, 10, 4882. [Google Scholar] [CrossRef] [PubMed] [PubMed Central]
  94. Thomassen, I.; van Gestel, Y.R.; van Ramshorst, B.; Luyer, M.D.; Bosscha, K.; Nienhuijs, S.W.; Lemmens, V.E.; de Hingh, I.H. Peritoneal carcinomatosis of gastric origin: A population-based study on incidence, survival and risk factors. Int. J. Cancer 2014, 134, 622–628. [Google Scholar] [CrossRef] [PubMed]
  95. Sugarbaker, P.H.; Cunliffe, W.J.; Belliveau, J.; de Bruijn, E.A.; Graves, T.; Mullins, R.E.; Schlag, P. Rationale for integrating early postoperative intraperitoneal chemotherapy into the surgical treatment of gastrointestinal cancer. Semin. Oncol. 1989, 16 (Suppl. S6), 83–97. [Google Scholar] [PubMed]
  96. Rau, B.; Lang, H.; Koenigsrainer, A.; Gockel, I.; Rau, H.G.; Seeliger, H.; Lerchenmueller, C.; Reim, D.; Wahba, R.; Angele, M.; et al. Effect of Hyperthermic Intraperitoneal Chemotherapy on Cytoreductive Surgery in Gastric Cancer with Synchronous Peritoneal Metastases: The Phase III GASTRIPEC-I Trial. J. Clin. Oncol. 2023, 42, JCO2202867. [Google Scholar] [CrossRef] [PubMed]
  97. Glehen, O.; Passot, G.; Villeneuve, L.; Vaudoyer, D.; Bin-Dorel, S.; Boschetti, G.; Piaton, E.; Garofalo, A. GASTRICHIP: D2 resection and hyperthermic intraperitoneal chemotherapy in locally advanced gastric carcinoma: A randomized and multicenter phase III study. BMC Cancer 2014, 14, 183. [Google Scholar] [CrossRef] [PubMed] [PubMed Central]
  98. Badgwell, B.D. Don’t Call It a Comeback-HIPEC for Gastric Cancer. Ann. Surg. Oncol. 2022, 29, 7244–7245. [Google Scholar] [CrossRef] [PubMed]
  99. van der Kaaij, R.T.; Wassenaar, E.C.E.; Koemans, W.J.; Sikorska, K.; Grootscholten, C.; Los, M.; Huitema, A.; Schellens, J.H.M.; Veenhof, A.; Hartemink, K.J.; et al. Treatment of PERItoneal disease in Stomach Cancer with cytOreductive surgery and hyperthermic intraPEritoneal chemotherapy: PERISCOPE I initial results. Br. J. Surg. 2020, 107, 1520–1528. [Google Scholar] [CrossRef] [PubMed]
  100. Gotze, T.O.; Piso, P.; Lorenzen, S.; Bankstahl, U.S.; Pauligk, C.; Elshafei, M.; Amato, G.; Reim, D.; Bechstein, W.O.; Konigsrainer, A.; et al. Preventive HIPEC in combination with perioperative FLOT versus FLOT alone for resectable diffuse type gastric and gastroesophageal junction type II/III adenocarcinoma—The phase III “PREVENT”—(FLOT9) trial of the AIO/CAOGI/ACO. BMC Cancer 2021, 21, 1158. [Google Scholar] [CrossRef] [PubMed] [PubMed Central]
  101. Gervaso, L.; Pellicori, S.; Cella, C.A.; Bagnardi, V.; Lordick, F.; Fazio, N. Biomarker evaluation in radically resectable locally advanced gastric cancer treated with neoadjuvant chemotherapy: An evidence reappraisal. Ther. Adv. Med. Oncol. 2021, 13, 17588359211029559. [Google Scholar] [CrossRef] [PubMed] [PubMed Central]
Cancers 16 01721 g001
Figure 1. Textbook Neoadjuvant Outcome components.
Figure 1. Textbook Neoadjuvant Outcome components.
Cancers 16 01721 g001
Table 1. Overview of TNO Components.
Table 1. Overview of TNO Components.
TNO CategoryDescription
Imaging **
 Complete Response *Disappearance of all target lesions, with any pathological lymph nodes diameter < 10 mm in short axis.
  Partial Response *At least a 30% decrease in the sum of diameters of target lesions, taking as reference the baseline sum diameters.
 Progressive DiseaseAt least a 20% increase in the sum of diameters of target lesions, taking as reference the smallest sum on study, as well as appearance of one or more new lesions.
  Stable Disease *Neither sufficient shrinkage to qualify for PR nor sufficient increase to qualify for PD, taking as reference the smallest sum diameter.
Timing to Surgery
 ≤4 weeks32% of mPR in European cohort [32]; twofold higher odds for achievement of mPR (OR 2.09; 95% CI 1.01–4.34, p = 0.047).
  4–6 weeks *Highest rate of ypT3-4 tumors (67.5%) and any postoperative complications (44.9%).
 >6 weeksHighest rate of lymphovascular invasion and ypN+ (62.5%), lowest rate of NAC completion (84.7%).
Nutrition
 BMI < 18.5 kg/m2
 BMI 18.5–25 kg/m2 *
 BMI > 25 kg/m2
  25–29.9 kg/m2
  >30 kg/m2
Underweight
Normal weight
Overweight
Pre-obesity
Obesity 		Cancers 16 01721 i001Among ESPEN criteria, BMI is the only one associated with prognosis; nutritional status deterioration may occur independently of body weight thus it should be assessed at early stage of oncologic treatment.
Laboratory Tests
 NLR ≤ 2 *
 NLR > 2
Low NLR; favorable prognosis, increased OS.
High NLR; decreased OS and PFS.
Treatment Toxicity
CTCAE v.5
  Grade 1 *Mild; no intervention needed, asymptomatic or mild symptoms.
  Grade 2 *Moderate; requires minimal intervention; affects age-appropriate instrumental ADL.
 Grade 3Severe or medically significant; not immediately life-threatening; requires hospitalization; affects self-care ADL.
 Grade 4Life-threatening consequences; requires urgent intervention.
 Grade 5Death related to adverse event.
TNO—Textbook Neoadjuvant Outcome; *—TNO Component; **—according to Computed Tomography or intraoperative assessment; mPR—major Pathological Response; OR—Odds Ratio; CI—Confidence Interval; ypT—post-neoadjuvant pathological tumor stage; ypN—post-neoadjuvant pathological nodal stage; BMI—Body Mass Index; ESPEN—European Society for Clinical Nutrition and Metabolism; NLR—Neutrophil-to-Lymphocyes Ratio; OS—Overall Survival; PFS—Progression Free Survival, CTCAE—Common Terminology Criteria for Adverse Events; ADL—Activities of Daily Living. Bold characteristics indicate TNO components
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Pelc, Z.; Sędłak, K.; Leśniewska, M.; Mielniczek, K.; Chawrylak, K.; Skórzewska, M.; Ciszewski, T.; Czechowska, J.; Kiszczyńska, A.; Wijnhoven, B.P.L.; et al. Textbook Neoadjuvant Outcome—Novel Composite Measure of Oncological Outcomes among Gastric Cancer Patients Undergoing Multimodal Treatment. Cancers 2024, 16, 1721. https://doi.org/10.3390/cancers16091721

AMA Style

Pelc Z, Sędłak K, Leśniewska M, Mielniczek K, Chawrylak K, Skórzewska M, Ciszewski T, Czechowska J, Kiszczyńska A, Wijnhoven BPL, et al. Textbook Neoadjuvant Outcome—Novel Composite Measure of Oncological Outcomes among Gastric Cancer Patients Undergoing Multimodal Treatment. Cancers. 2024; 16(9):1721. https://doi.org/10.3390/cancers16091721

Chicago/Turabian Style

Pelc, Zuzanna, Katarzyna Sędłak, Magdalena Leśniewska, Katarzyna Mielniczek, Katarzyna Chawrylak, Magdalena Skórzewska, Tomasz Ciszewski, Joanna Czechowska, Agata Kiszczyńska, Bas P. L. Wijnhoven, and et al. 2024. "Textbook Neoadjuvant Outcome—Novel Composite Measure of Oncological Outcomes among Gastric Cancer Patients Undergoing Multimodal Treatment" Cancers 16, no. 9: 1721. https://doi.org/10.3390/cancers16091721

APA Style

Pelc, Z., Sędłak, K., Leśniewska, M., Mielniczek, K., Chawrylak, K., Skórzewska, M., Ciszewski, T., Czechowska, J., Kiszczyńska, A., Wijnhoven, B. P. L., Van Sandick, J. W., Gockel, I., Gisbertz, S. S., Piessen, G., Eveno, C., Bencivenga, M., De Manzoni, G., Baiocchi, G. L., Morgagni, P., ... Rawicz-Pruszyński, K. (2024). Textbook Neoadjuvant Outcome—Novel Composite Measure of Oncological Outcomes among Gastric Cancer Patients Undergoing Multimodal Treatment. Cancers, 16(9), 1721. https://doi.org/10.3390/cancers16091721

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop