Incidence of Capillary Leak Syndrome as an Adverse Effect of Drugs in Cancer Patients: A Systematic Review and Meta-Analysis

Capillary leak syndrome (CLS) is a rare disease with profound vascular leakage, which can be associated with a high mortality. There have been several reports on CLS as an adverse effect of anti-cancer agents and therapy, but the incidence of CLS according to the kinds of anti-cancer drugs has not been systemically evaluated. Thus, the aim of our study was to comprehensively meta-analyze the incidence of CLS by different types of cancer treatment or after bone marrow transplantation (BMT). We searched the literatures (inception to July 2018) and among 4612 articles, 62 clinical trials (studies) were eligible. We extracted the number of patients with CLS, total cancer patients, name of therapeutic agent and dose, and type of cancer. We performed a meta-analysis to estimate the summary effects with 95% confidence interval and between-study heterogeneity. The reported incidence of CLS was categorized by causative drugs and BMT. The largest number of studies reported on CLS incidence during interleukin-2 (IL-2) treatment (n = 18), which yielded a pooled incidence of 34.7% by overall estimation and 43.9% by meta-analysis. The second largest number of studies reported on anti-cluster of differentiation (anti-CD) agents (n = 13) (incidence of 33.9% by overall estimation and 35.6% by meta-analysis) or undergoing BMT (n = 7 (21.1% by overall estimation and 21.7% by meta-analysis). Also, anti-cancer agents, including IL-2 + imatinib mesylate (three studies) and anti-CD22 monoclinal antibodies (mAb) (four studies), showed a dose-dependent increase in the incidence of CLS. Our study is the first to provide an informative overview on the incidence rate of reported CLS patients as an adverse event of anti-cancer treatment. This meta-analysis can lead to a better understanding of CLS and assist physicians in identifying the presence of CLS early in the disease course to improve the outcome and optimize management.


Rationale
3 Describe the rationale for the review in the context of what is already known.

5
Objectives 4 Provide an explicit statement of questions being addressed with reference to participants, interventions, comparisons, outcomes, and study design (PICOS).

METHODS
Protocol and registration 5 Indicate if a review protocol exists, if and where it can be accessed (e.g., Web address), and, if available, provide registration information including registration number.
N/A Eligibility criteria 6 Specify study characteristics (e.g., PICOS, length of follow-up) and report characteristics (e.g., years considered, language, publication status) used as criteria for eligibility, giving rationale.

6
Information sources 7 Describe all information sources (e.g., databases with dates of coverage, contact with study authors to identify additional studies) in the search and date last searched.

6-8
Search 8 Present full electronic search strategy for at least one database, including any limits used, such that it could be repeated.

6-8
Study selection 9 State the process for selecting studies (i.e., screening, eligibility, included in systematic review, and, if applicable, included in the meta-analysis).
6-8 Figure 1 Data collection process 10 Describe method of data extraction from reports (e.g., piloted forms, independently, in duplicate) and any processes for obtaining and confirming data from investigators.

6-8
Data items 11 List and define all variables for which data were sought (e.g., PICOS, funding sources) and any assumptions and simplifications made.

6-8
Risk of bias in individual studies 12 Describe methods used for assessing risk of bias of individual studies (including specification of whether this was done at the study or outcome level), and how this information is to be used in any data synthesis.

N/A
Summary measures 13 State the principal summary measures (e.g., risk ratio, difference in means).

8-9
Synthesis of results 14 Describe the methods of handling data and combining results of studies, if done, including measures of consistency (e.g., I 2 ) for each meta-analysis.

8-9
Section/topic # Checklist item Reported on page # Risk of bias across studies 15 Specify any assessment of risk of bias that may affect the cumulative evidence (e.g., publication bias, selective reporting within studies).

N/A
Additional analyses 16 Describe methods of additional analyses (e.g., sensitivity or subgroup analyses, meta-regression), if done, indicating which were pre-specified.

Study selection
17 Give numbers of studies screened, assessed for eligibility, and included in the review, with reasons for exclusions at each stage, ideally with a flow diagram.
9 Figure 1 Study characteristics 18 For each study, present characteristics for which data were extracted (e.g., study size, PICOS, follow-up period) and provide the citations.

9
Risk of bias within studies 19 Present data on risk of bias of each study and, if available, any outcome level assessment (see item 12).

N/A
Results of individual studies 20 For all outcomes considered (benefits or harms), present, for each study: (a) simple summary data for each intervention group (b) effect estimates and confidence intervals, ideally with a forest plot.

DISCUSSION
Summary of evidence 24 Summarize the main findings including the strength of evidence for each main outcome; consider their relevance to key groups (e.g., healthcare providers, users, and policy makers).

19-22
Limitations 25 Discuss limitations at study and outcome level (e.g., risk of bias), and at review-level (e.g., incomplete retrieval of identified research, reporting bias).

22
Conclusions 26 Provide a general interpretation of the results in the context of other evidence, and implications for future research. Supplementary Figure S1. Forest plot of meta-analysis to estimate the incidence of capillary leak syndrome according to various anti-cancer treatments

22-23
Supplementary Figure S1(a). Forest plot of random effects meta-analysis to estimate the incidence of capillary leak syndrome in cancer patients who received interleukin-2.
Supplementary Figure S1(b). Forest plot of random effects meta-analysis to estimate the incidence of capillary leak syndrome in cancer patients who received interleukin-2 with other agents.
Supplementary Figure S1(c). Forest plot of random effects meta-analysis to estimate the incidence of capillary leak syndrome in cancer patients who received interleukin-2 with interferon-alpha.
Supplementary Figure S1(d). Forest plot of random effects meta-analysis to estimate the incidence of capillary leak syndrome in cancer patients who received interleukin-1 with other agents.
Supplementary Figure S1(e). Forest plot of random effects meta-analysis to estimate the incidence of capillary leak syndrome in cancer patients who received interleukin-2 with imatinib mesylate.
Supplementary Figure S1(f). Forest plot of random effects meta-analysis to estimate the incidence of capillary leak syndrome in cancer patients who received interleukin-2 with bevacizumab.
Supplementary Figure S1(g). Forest plot of random effects meta-analysis to estimate the incidence of capillary leak syndrome in cancer patients who received interleukin-2 and 5-fluorouracil.
Supplementary Figure S1(h). Forest plot of random effects meta-analysis to estimate the incidence of capillary leak syndrome in cancer patients who received GM-CSF.
Supplementary Figure S1(j). Forest plot of random effects meta-analysis to estimate the incidence of capillary leak syndrome in cancer patients who received SS1P.
Supplementary Figure S1(l). Forest plot of random effects meta-analysis to estimate the incidence of capillary leak syndrome in cancer patients who received anti-CD22 agents.
Supplementary Figure S1(m). Forest plot of random effects meta-analysis to estimate the incidence of capillary leak syndrome in cancer patients who received anti-CD19 + anti-CD22 agents.
Supplementary Figure S1(n). Forest plot of random effects meta-analysis to estimate the incidence of capillary leak syndrome in cancer patients who received anti-CD25 agents.