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Cancers
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Cancer Survivors: Late Effects of Cancer Therapy
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Cancer Survivors: Late Effects of Cancer Therapy

A special issue of Cancers (ISSN 2072-6694). This special issue belongs to the section "Cancer Survivorship and Quality of Life".

Deadline for manuscript submissions: 30 September 2026 | Viewed by 2220

Special Issue Editor

Dr. Gaurav Kumar

E-Mail Website
Guest Editor
TSET Health Promotion Research Center, Stephenson Cancer Center, The University of Oklahoma Health Sciences, 655 Research Parkway, 400, Oklahoma City, OK 73104, USA
Interests: health promotion among diverse communities; cancer care; behavior change research

Special Issue Information

Dear Colleagues,

Cancer survivors are increasingly encountering a range of late effects that can emerge months to years after completing primary therapy. These delayed toxicities, encompassing heart and lung damage, secondary malignancies, endocrine disorders, cognitive decline, chronic fatigue, and emotional distress, can emerge months or even decades after treatment. Historically, survivorship care has focused on acute side effects and recurrence surveillance, often leaving these long-term sequelae unrecognized and unaddressed, thereby exposing patients to preventable morbidity. Therefore, emphasizing late effects is crucial to bridging gaps in care: early identification, risk-stratified monitoring, and evidence-based interventions can mitigate lasting harm, enhance quality of life, and ensure optimal survivorship.

As our knowledge of cancer survivorship deepens, it is essential to bridge research and practice by developing evidence-based interventions that seamlessly integrate into clinical routines. Empowering survivors with these tools not only aids in extending life but also enhances its quality and satisfaction. This Special Issue will feature original research articles and comprehensive reviews that deepen our understanding of the late and post-treatment impacts of cancer therapy.

Dr. Gaurav Kumar
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Cancers is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2900 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • late effects
  • cancer survivorship
  • treatment toxicity
  • long-term outcomes

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Published Papers (2 papers)

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Research

19 pages, 330 KB  
Article
Perceived Barriers and Facilitators to Physical Activity Engagement Among Cancer Survivors: A Qualitative Study
by Gaurav Kumar, Priyanka Chaudhary, Apar Kishor Ganti, Jungyoon Kim, Lynette M. Smith and Dejun Su
Cancers 2026, 18(5), 817; https://doi.org/10.3390/cancers18050817 - 3 Mar 2026
Viewed by 593
Abstract
Background: Although physical activity (PA) offers substantial physical and psychosocial benefits, engagement remains suboptimal among cancer survivors. A theory-informed understanding of survivors’ perceived barriers, facilitators, and recommendations is needed to inform patient-centered PA about survivorship interventions. Objective: This study aimed to explore perceived [...] Read more.
Background: Although physical activity (PA) offers substantial physical and psychosocial benefits, engagement remains suboptimal among cancer survivors. A theory-informed understanding of survivors’ perceived barriers, facilitators, and recommendations is needed to inform patient-centered PA about survivorship interventions. Objective: This study aimed to explore perceived barriers, facilitators, and recommendations for PA engagement among adult cancer survivors using the Theoretical Domains Framework (TDF). Methods: A phenomenological qualitative design was used. Eighteen cancer survivors from Nebraska participated in semi-structured interviews via Zoom or telephone. Semi-structured interviews (guided by open-ended questions with flexibility for probing) were transcribed verbatim, imported into MAXQDA 2024, and analyzed using TDF to identify themes and subthemes. Results: Three overarching themes emerged: barriers, facilitators, and recommendations related to PA engagement. Barriers included individual factors (low motivation and self-efficacy, limited awareness of PA guidelines, time constraints, and physical limitations due to treatment and comorbidities), social factors (limited support from family, friends), clinical factors (limited PA guidance from healthcare providers), and environmental factors (restricted access to resources and unfavorable weather). Facilitators included individual factors (PA knowledge, motivation, goals, and health benefits), social factors (support from family, friends), and clinical factors (encouragement from healthcare providers), and environmental factors (favorable weather and available community PA resources). Recommendations emphasized the need for tailored education, supportive counseling, and structured PA programs within survivorship care. Conclusions: Cancer survivors described multilevel determinants of PA engagement across individual, social, and environmental contexts. Findings highlight the importance of theory-informed, patient-centered strategies that enhance PA guideline awareness, strengthen social and clinical support, and improve access to community resources to promote sustained PA during cancer survivorship. Full article
(This article belongs to the Special Issue Cancer Survivors: Late Effects of Cancer Therapy)
22 pages, 3518 KB  
Article
Dose-Guided Hybrid AI Model with Deep and Handcrafted Radiomics for Explainable Radiation Dermatitis Prediction in Breast Cancer VMAT
by Tsair-Fwu Lee, Ling-Chuan Chang-Chien, Lawrence Tsai, Chia-Hui Chen, Po-Shun Tseng, Jun-Ping Shiau, Yang-Wei Hsieh, Shyh-An Yeh, Cheng-Shie Wuu, Yu-Wei Lin and Pei-Ju Chao
Cancers 2025, 17(23), 3767; https://doi.org/10.3390/cancers17233767 - 26 Nov 2025
Cited by 1 | Viewed by 1186
Abstract
Purpose: To improve the prediction accuracy of radiation dermatitis (RD) in breast cancer patients undergoing volumetric modulated arc therapy (VMAT), we developed a hybrid artificial intelligence (AI) model that integrates deep learning radiomics (DLR), handcrafted radiomics (HCR), clinical features, and dose–volume histogram (DVH) [...] Read more.
Purpose: To improve the prediction accuracy of radiation dermatitis (RD) in breast cancer patients undergoing volumetric modulated arc therapy (VMAT), we developed a hybrid artificial intelligence (AI) model that integrates deep learning radiomics (DLR), handcrafted radiomics (HCR), clinical features, and dose–volume histogram (DVH) parameters, aiming to enhance the early identification of high-risk individuals and support personalized prevention strategies. Methods: A retrospective cohort of 156 breast cancer patients treated with VMAT at Kaohsiung Veterans General Hospital (2018–2023) was analyzed; 148 patients were eligible after exclusions, with RD graded according to the RTOG criteria. Clinical variables and 12 DVH indices were collected, while HCR features were extracted via PyRadiomics. DLR features were derived from a pretrained VGG16 network across four input designs: original CT images (DLROriginal), a 5 mm subcutaneous region (DLRSkin5mm), a planning target volume with a 100% prescription dose (DLRPTV100%), and a subcutaneous region receiving ≥ 5 Gy (DLRV5Gy). The features were preselected via ANOVA (p < 0.05), followed by Boruta–SHAP refinement across 11 feature sets. Predictive models were built via logistic regression, random forest, gradient boosting decision tree, and stacking ensemble (SE) methods. Explainability was assessed via SHapley Additive exPlanations (SHAPs) and gradient-weighted class activation mapping (Grad-CAM). Results: Among the 148 patients, 49 (33%) developed Grade ≥ 2 RD. The DLR models outperformed the HCR models (AUC = 0.72 vs. 0.66). The best performance was achieved with DLRV5Gy + clinical + DVH features, yielding an AUC = 0.76, recall = 0.68, and F1 score = 0.60. SE consistently surpassed single classifiers. SHAP identified convolutional DLR features as the strongest predictors, whereas Grad-CAM focused attention on subcutaneous high-dose regions, which was consistent with the clinical RD distribution. Conclusions: The proposed hybrid AI framework, which integrates DLR, clinical, and DVH features, provides accurate and explainable predictions of Grade ≥ 2 RD after VMAT in breast cancer patients. By combining ensemble learning with XAI methods, the model offers reliable high-risk stratification and potential clinical utility for personalized treatment planning. Full article
(This article belongs to the Special Issue Cancer Survivors: Late Effects of Cancer Therapy)
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