Using biological information and biomarkers to improve health care for specific patient subgroups

Summary
“Personalized medicine” or “stratified medicine” includes the assessment of subgroup effects for particular patient groups. This line of research addresses the need for evidence-based guidance on the assessment of subgroup claims and analyses in clinical trials or meta-analyses, on methodological approaches to examine continuous variables as effect modifiers, and the planning and reporting of subgroup analyses. Using a recently developed, user-tested assessment tool (ICEMAN), we are currently investigating studies on target-specific anti-cancer drugs.

Publications

• Schandelmaier S, Schmitt AM, Herbrand AK, Glinz D, Ewald H, Briel M, Guyatt GH, Hemkens LG, Kasenda B. Characteristics and interpretation of subgroup analyses based on tumor characteristics in randomized trials testing targeted-specific anti-cancer drugs: design of a systematic survey. BMJ Open 2020;10(5):e034565
• Schandelmaier S, Briel M, Varadhan R, Schmid CH, Devasenapathy N, Hayward RA, Gagnier J, Borenstein M, van der Heijden GJMG, Dahabreh IJ, Sun X, Sauerbrei W, Walsh MW, Ioannidis JPA, Thabane L, Guyatt GH. Development of a new Instrument to assess the Credibility of Effect Modification Analyses (ICEMAN) in randomized controlled trials and meta-analyses. CMAJ 2020 (in press)
• Schandelmaier S, Chang Y, Devasenapathy N, Devji T, Kwong J, Colunga Lozano LE, Lee Y, Agarwal A, Bhatnagar N, Ewald H, Zhang Y, Sun X, Thabane L, Walsh M, Briel M, Guyatt GH. A systematic survey identified 36 criteria for assessing effect modification claims in randomized trials or meta-analyses. J Clin Epidemiol 2019;113:159-167
• Kasenda B, Sauerbrei W, Royston P, Mercat A, Brower RG, Slutsky AS, Cook D, Guyatt GH, Brochard L, Richard JCM, Stewart TE, Meade MO, Briel M. Multivariable Fractional Polynomial Interaction to Investigate Continuous Effect Modifiers in a meta-analysis on higher versus lower PEEP for patients with ARDS. BMJ Open 2016;6(9):e011148
• Kasenda B, Schandelmaier S, Sun X, von Elm E, You J, Blümle A, Tomonaga Y, Saccilotto R, Amstutz A, Bengough T, Meerpohl J, Stegert M, Olu KK, Tikkinen KAO, Neumann I, Carrasco-Labra A, Faulhaber M, Mulla S, Mertz D, Akl EA, Bassler D, Busse J, Ferreira-González I, Lamontagne F, Nordmann AJ, Gloy V, Raatz H, Moja L, Rosenthal R, Ebrahim S, Vandvik PO, Johnston BC, Walter MA, Burnand B, Schwenkglenks M, Hemkens L, Bucher HC, Guyatt GH, Briel M. Subgroup analyses in randomised controlled trials: cohort study on trial protocols and journal publications. BMJ 2014;349:g4539
• Sun X, Briel M, Busse JW, You JJ, Akl EA, Mejza F, Bala MM, Bassler D, Mertz D, Diaz-Granados N, Vandvik PO, Malaga G, Srinathan SK, Dahm P, Johnston BC, Alonso-Coello P, Hassouneh B, Walter SD, Heels-Ansdell D, Bhatnagar N, Altman DG, Guyatt GH. Claims of subgroup effects in randomized controlled trials: are they believable? Systematic review. BMJ 2012;344:e1553
• Sun X, Briel M, Busse JW,You JJ, Akl EA, Mejza F, Bala M, Bassler D, Mertz D, Diaz-Granados N, Vandvik PO, Malaga G, Srinathan SK, Dahm P, Johnston BC, Alonso-Coello P, Hassouneh B, Walter SD, Heels-Ansdell D, Altman DG, Guyatt GH. The influence of study characteristics on reporting of subgroup analyses in randomized controlled trials. BMJ 2011;342:d1569
• Sun X, Briel M, Walter SD, Guyatt GH. Is a subgroup effect believable? Updating criteria to evaluate the credibility of subgroup analyses. BMJ 2010;340:c117

Basel research team
Stefan Schandelmaier, Benjamin Kasenda, Matthias Briel