{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,7]],"date-time":"2026-10-07T17:49:28Z","timestamp":1791395368429,"version":"4.3.3"},"reference-count":58,"publisher":"Becaris Publishing Limited","issue":"7","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["J. Comp. Eff. Res."],"published-print":{"date-parts":[[2026,7]]},"abstract":"<jats:p>\n                    <jats:bold>Aim:<\/jats:bold>\n                    Several CAR-T cell therapies have received regulatory approval from both the US FDA and the EMA for the treatment of large B-cell lymphoma. However, direct comparative trials between CAR-T cell therapies are lacking, mainly due to different clinical development timelines and availabilities as well as substantial resource requirements and difficulties in recruiting sufficiently large and homogeneous cohorts from a highly pre-treated patient population. Consequently, indirect treatment comparisons (ITCs) play a critical role in evaluating the relative benefits of CAR-T cell therapies. However, ITCs are inherently susceptible to confounding, underscoring the importance of systematically identifying and appropriately adjusting for key prognostic factors, and treatment effect modifiers.\n                    <jats:bold>Materials &amp; methods:<\/jats:bold>\n                    A systematic literature search was conducted in PubMed\/MEDLINE, EMBASE and the Cochrane Central Register of Controlled Trials (CENTRAL) in November 2025. Database-specific search strategies using controlled vocabulary (MeSH and Emtree) were applied. Records were deduplicated prior to screening. Studies published in English or German were eligible. Two reviewers independently screened titles\/abstracts and full texts using predefined criteria, with disagreements resolved by consensus.\n                    <jats:bold>Results:<\/jats:bold>\n                    A total of 27 publications met the inclusion criteria. Most studies used unanchored matching-adjusted indirect comparisons, followed by propensity score-based methods and network meta-analyses. The extent of covariate adjustment varied widely, ranging from no adjustment to extensive multivariable adjustment with up to 19 covariates. Commonly adjusted factors included demographics, disease severity, clinical status and treatment history. Efficacy outcomes most frequently assessed overall and progression-free survival and response rates, whereas safety outcomes were reported less consistently and were rarely covariate-adjusted, limiting comparative interpretation. Covariates were selected based on clinical expertise and\/or literature review; however, no study provided a detailed description of the identification methodology.\n                    <jats:bold>Conclusion:<\/jats:bold>\n                    Although the selection of variables for adjustment frequently targeted recognized prognostic factors, the underlying processes lacked methodological transparency and were often constrained by data availability or undocumented expert opinion. Consequently, this resulted in substantial heterogeneity across studies. Notably, even fundamental covariates routinely required in health technology assessments, such as age, sex and disease severity, were inconsistently addressed, further limiting the comparability and robustness of the reported ITCs. To enhance the reliability and comparability of ITC results, standardized approaches for covariate identification and adjustment are urgently needed.\n                  <\/jats:p>","DOI":"10.57264\/cer-2026-0033","type":"journal-article","created":{"date-parts":[[2026,6,26]],"date-time":"2026-06-26T12:11:34Z","timestamp":1782475894000},"source":"Crossref","is-referenced-by-count":1,"title":["Covariate selection and adjustment for efficacy and safety endpoints in indirect comparative effectiveness analyses of CAR-T-cell therapies for large B-cell lymphoma: a systematic review"],"prefix":"10.57264","volume":"15","author":[{"given":"Marie A-C","family":"Neumann","sequence":"first","affiliation":[{"name":"Department I of Internal Medicine, Center for Integrated Oncology Aachen Bonn Cologne Duesseldorf (CIO ABCD), Faculty of Medicine &amp; University Hospital of Cologne, University of Cologne, Cologne, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jonas","family":"Jost","sequence":"additional","affiliation":[{"name":"MArS Market Access &amp; Pricing Strategy GmbH, Geffelbachstra\u00dfe 6, 79576, Weil Am Rhein, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sybille","family":"Riou","sequence":"additional","affiliation":[{"name":"Miltenyi Biomedicine, Friedrich-Ebert-Stra\u00dfe 68, 51429 Bergisch Gladbach, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Stefanie","family":"Rungaldier","sequence":"additional","affiliation":[{"name":"Miltenyi Biomedicine, Friedrich-Ebert-Stra\u00dfe 68, 51429 Bergisch Gladbach, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Stefan","family":"Walzer","sequence":"additional","affiliation":[{"name":"MArS Market Access &amp; Pricing Strategy GmbH, Geffelbachstra\u00dfe 6, 79576, Weil Am Rhein, Germany"},{"name":"University of Applied Sciences, Weingarten-Ravensburg, Germany"},{"name":"State University Baden-Wuerttemberg, Hangstra\u00dfe 46-50, 79539, L\u00f6rrach, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1110-2793","authenticated-orcid":false,"given":"J\u00f6rg","family":"Mahlich","sequence":"additional","affiliation":[{"name":"Miltenyi Biomedicine, Friedrich-Ebert-Stra\u00dfe 68, 51429 Bergisch Gladbach, Germany"},{"name":"DICE; Heinrich-Heine-University D\u00fcsseldorf, Universit\u00e4tsstra\u00dfe 1, 40225 D\u00fcsseldorf, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"36897","reference":[{"key":"e_1_3_6_3_2","doi-asserted-by":"crossref","first-page":"565236","DOI":"10.3389\/fimmu.2020.565236","article-title":"Cancer immunotherapy using chimeric antigen receptor expressing T-Cells: present and future needs of clinical cancer centers","volume":"11","author":"Gotti M","year":"2020","unstructured":"Gotti M, Defrancesco I, D'Angelo M Cancer immunotherapy using chimeric antigen receptor expressing T-Cells: present and future needs of clinical cancer centers. 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