1166 International Journal of Stroke 18(10) Figure 2. Scatterplot of sample size against the number of subgroup effects analyzed. Table 2. Characteristics of subgroup effect reported in trial publications (n = 647). Characteristics Prespecified subgroup effect: n (%) Acute stroke treatment Primary prevention Secondary prevention Prespecified subgroup effect: n (%) Yes No Was the subgroup effect described? n (%) Yes No Figure 3. Trend analysis of quality of reporting among the included studies. Was direction effect anticipated: n (%) Yes No N (%) 319 (49) 114 (18) 214 (33) 421 (65) 226 (35) 354 (55) 293 (45) 6 (1) 641 (99) Arbitrary categorized of continuous subgroup effectsa: n (%) Yes No Not applicable Was statistical power considered? n (%) Yes No Is subgroup effect significant? n (%) Yes No The poor credibility of report subgroup analyses highlights the need for a multipronged approach to address this issue. Regrettably, the low credibility of published subgroup analyses observed in this review of stroke trials is consistent with findings from systematic reviews of published trials in other disciplines. The used of the ICEMAN checklist in other studies have showed that subgroup effects had a very low to low credibility rating. Kilpeläinen et al.22 criticized the poor conduct and reporting of subgroup analyses in urology trials. Using data from the well-known Prostate Cancer Intervention Versus Observation Trial (PIVOT) trial31 that has influenced clinical practice guidelines,32 they demonstrated the use of ICEMAN for assessing the credibility of findings from subgroup analyses and argued that results of subgroup analysis of this trial had low International Journal of Stroke, 18(10) 237 (37) 12 (2) 398 (61) 185 (29) 462 (71) 40 (6) 607 (94) aCategorized the subgroup effect without providing justification. credibility rating. Furthermore, Saragiotto et al.33 examine the credibility of subgroup analyses in back pain trials and concluded that subgroup analyses in these published trials had low credibility rating. Similarly, Wallach et al.34 discovered that efforts to verify statistically significant subgroup differences claimed in many RCTs are uncommon, and when they do occur, the claimed subgroup differences are not replicated. Here we provide a few recommendations to address this issue. First, there is need for more education of trialists on the best methods for performing subgroup analyses to minimize misleading results. Given that many reported subgroup analyses are underpowered, biological and sample size considerations should be used to guide the selection of few subgroups that will be conducted to avoid