The following protocol has been written according to the MOOSE Guidelines for Meta-Analyses and Systematic Reviews of Observational Studies and the PRISMA-P (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines (17, 18). The protocol has been registered at the International Prospective Register of Systematic Reviews (PROSPERO; registration number: CRD42020166770).
Data sources search terms and search strategy
To achieve the study objectives, searches will be carried out in the following electronic databases: PubMed, Scopus, Web of Science, Web of Conferences, Open Grey. The following search terms will be used in literature review: (“chronic lymphocytic leukemia” OR “well-differentiated lymphocytic lymphoma” OR “small lymphocytic lymphoma” OR “small-cell lymphoma” OR “chronic Lymphoblastic Leukemia” OR “Lymphocytic Lymphoma” OR “Chronic B-Cell Leukemia” OR “Chronic B-Lymphocytic Leukemia” OR “CLL” OR “low-grade lymphoma”) AND (“tumor lysis syndrome” OR “tumor lysis syndrome” OR “TLS”
Reference lists of key full-text and any reports that may be eligible will be reviewed for publications included in the study. The systematic method specifies that all published research constitute the literature search on CLL and TLS. The search strategy is considered adequate to reduce the risk of selection and detection bias. The search results will be exported to Endnote where duplicates are excluded. Included studies will be manually screened to select other relevant studies.
A populated PRISMA-P checklist was used as an aid to authors to clearly, completely, and transparently let reviewers and readers know what authors intend to do (19).
Inclusion and exclusion criteria
Eligible studies should report the empirical incidence of TLS in CLL patients treated with novel and/or conventional therapies. All literature including clinical trials, case reports, case series, and abstracts from 2009 to 2020 in the English language will be included. Data based on conference abstracts and gray literature (e.g., reports, etc.) will also be included. Studies in languages other than English will not be included.
The study population will include adult (18 years or older) patients diagnosed with CLL diagnosis and received treatment. Exclusion criteria include patients aged less than 19 years, known active histological transformation from CLL to an aggressive lymphoma (i.e., Richter’s transformation), other diagnoses of active cancer or the presence of other active malignancy or the use of systemic therapy for another malignancy within 3 years; local/regional therapy with curative intent years of treatment is permitted.
Data extraction (selection and coding)
Two reviewers will independently assess eligibility of all the citations described and extracted data from the original trial reports using a limited data extraction method including the study details for example publication year, authors, study design, clinicalTrials.gov Identifier code, follow-up duration), patient characteristics (inclusion and exclusion criteria and other various related features), sample size and the details of interventions/comparisons, primary and secondary outcome measures, and subgroup/stratified statistical analyses reported included.
Statistical evaluation of both safety and efficacy parameters using various statistical measures such as hazard ratios (HRs), progression-free survival (PFS), and overall survival (OS) between different treatments will be reported.
To minimize any data entry error, all data will be entered in duplicate and cross-checked for accuracy, and disparities would be discussed in a team meeting. Assessment of study quality or strength of study will be carried out as well (high, moderate, low)
Assessment of methodological quality (risk of bias)
Study quality will be evaluated by two reviewers using the statistical methodology and categories described in the Cochrane Collaboration Handbook and PRISMA and other applicable guidelines. In case of disagreement, a team meeting/group discussion will be conducted to reach a consensus. Other potential issues will also be considered that includes baseline imbalance and the other potential issues. The cumulative evidence might be affected by bias (e.g., publication bias, selective reporting within studies) will be evaluated. Risk of bias that might affect the cumulative evidence (such as publication bias, selective reporting within studies) will be assessed with plotting the effect by the inverse of its standard error. The symmetry of such ‘funnel plots’ (using applicable standard statistical software like CMA and STATA etc.) will be assessed both visually, and formally with Egger’s test, to see if the effect decreased with increasing sample size.
Meta-analytic approach
The meta-analysis will be performed and conducted using applicable standard statistical software like CMA and STATA etc. Confidence intervals will be set at 95%. The inter‐study heterogeneity will be evaluated with the inconsistency index (I2). When significant heterogeneity is present (I2>50%), a random-effects model will be implemented to calculate pooled estimates of specific effect size measures along with the 95% confidence intervals (95% CI).
Subgroup analysis will be conducted depending on potential factors and covariates that might affect mainly primary outcome measures. Sensitivity analysis will be performed to investigate the effect of individual studies concerning the primary outcome measures of the meta‐analysis.
A network meta-analysis will be conducted to compare the treatment outcomes between conventional treatments and several novel targeted agents, and all results will be reported according to the PRISMA extension statement for network meta-analyses.
A network meta-analysis combines direct and indirect estimates of relative treatment effects in one statistical analysis.
A network plot will be produced to represent the data from all trials included in the analysis. The contribution of each direct comparison to the network estimate will be calculated according to the variance of the direct treatment effect and the network structure, later summarized in a contribution plot.
A forest plot of the estimated summary effects, along with CIs for all comparisons, summarizes the relative mean effect or other effect size measure and prediction on each comparison in one plot.
Statistical analysis based on potential subgroups and stratifications (e.g., stage and severity of the disease, age group, gender, clinical significance, and co-morbidity etc.) that might affect primary outcome measures.