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Rationale, aims and objectives: New therapies are increasingly approved by regulatory agencies such as the Food and Drug Administration (FDA) and the European Medicines Agency (EMA) based on testing in non‐randomized clinical trials. These treatments have typically displayed "dramatic effects" (ie, effects that are considered large enough to obviate the combined effects of biases and random errors that may affect the study results). The agencies, however, have not identified how large these effects should be to avoid the need for further testing in randomized controlled trials (RCTs). We investigated the effect size that would circumvent the need for further RCTs testing by the regulatory agencies. We hypothesized that the approval of therapeutic interventions by regulators is based on heuristic decision making whose accuracy can be best characterized by the application of signal detection theory (SDT). Methods: We merged the EMA and FDA database of approvals based on non‐RCT comparisons. We excluded duplicate entries between the two databases. We included a total of 134 approvals of drugs and devices based on non‐RCTs. We integrated Weber‐Fechner law of psychophysics and recognition heuristics within SDT to provide descriptive explanations of the decisions made by the FDA and EMA to approve new treatments based on non‐randomized studies without requiring further testing in RCTs. Results: Our findings suggest that when the difference between novel treatments and the historical control is at least one logarithm (base 10) of magnitude, the veracity of testing in non‐RCTs seems to be established. Conclusion: Drug developers and practitioners alike can use the change in one logarithm of effect size as a benchmark to decide if further testing in RCTs should be pursued, or as a guide to interpreting the results reported in non‐randomized studies. However, further research would be useful to better characterize the threshold of effect size above which testing in RCTs is not needed. [ABSTRACT FROM AUTHOR]

Abstract Background Lung cancer is considered a terminal illness with a five-year survival rate of about 16%. Informed decision-making related to the management of a disease requires accurate prognosis of the disease with or without treatment. Despite the significance of disease prognosis in clinical decision-making, systematic assessment of prognosis in patients with lung cancer without treatment has not been performed. We conducted a systematic review and meta-analysis of the natural history of patients with confirmed diagnosis of lung cancer without active treatment, to provide evidence-based recommendations for practitioners on management decisions related to the disease. Specifically, we estimated overall survival when no anticancer therapy is provided. Methods Relevant studies were identified by search of electronic databases and abstract proceedings, review of bibliographies of included articles, and contacting experts in the field. All prospective or retrospective studies assessing prognosis of lung cancer patients without treatment were eligible for inclusion. Data on mortality was extracted from all included studies. Pooled proportion of mortality was calculated as a back-transform of the weighted mean of the transformed proportions using the random-effects model. To perform meta-analysis of median survival, published methods were used to pool the estimates as mean and standard error under the random-effects model. Methodological quality of the studies was examined. Results Seven cohort studies (4,418 patients) and 15 randomized controlled trials (1,031 patients) were included in the meta-analysis. All studies assessed mortality without treatment in patients with non-small cell lung cancer (NSCLC). The pooled proportion of mortality without treatment in cohort studies was 0.97 (95% CI: 0.96 to 0.99) and 0.96 in randomized controlled trials (95% CI: 0.94 to 0.98) over median study periods of eight and three years, respectively. When data from cohort and randomized controlled trials were combined, the pooled proportion of mortality was 0.97 (95% CI: 0.96 to 0.98). Test of interaction showed a statistically non-significant difference between subgroups of cohort and randomized controlled trials. The pooled mean survival for patients without anticancer treatment in cohort studies was 11.94 months (95% CI: 10.07 to 13.8) and 5.03 months (95% CI: 4.17 to 5.89) in RCTs. For the combined data (cohort studies and RCTs), the pooled mean survival was 7.15 months (95% CI: 5.87 to 8.42), with a statistically significant difference between the two designs. Overall, the studies were of moderate methodological quality. Conclusion Systematic evaluation of evidence on prognosis of NSCLC without treatment shows that mortality is very high. Untreated lung cancer patients live on average for 7.15 months. Although limited by study design, these findings provide the basis for future trials to determine optimal expected improvement in mortality with innovative treatments.

Abstract Background Despite advances in understanding of clinical, genetic, and molecular aspects of multiple myeloma (MM) and availability of more effective therapies, MM remains incurable. The autologous-allogeneic (auto-allo) hematopoietic cell transplantation (HCT) strategy is based on combining cytoreduction from high-dose (chemo- or chemoradio)-therapy with adoptive immunotherapy. However, conflicting results have been reported when an auto-allo HCT approach is compared to tandem autologous (auto-auto) HCT. A previously published meta-analysis has been reported; however, it suffers from serious methodological flaws. Methods A systematic search identified 152 publications, of which five studies (enrolling 1538 patients) met inclusion criteria. All studies eligible for inclusion utilized biologic randomization. Results Assessing response rates by achievement of at least a very good partial response did not differ among the treatment arms [risk ratio (RR) (95% CI) = 0.97 (0.87-1.09), p = 0.66]; but complete remission was higher in the auto-allo HCT arm [RR = 1.65 (1.25-2.19), p = 0.0005]. Event-free survival did not differ between auto-allo HCT group versus auto-auto HCT group using per-protocol analysis [hazard ratio (HR) = 0.78 (0.58-1.05)), p = 0.11] or using intention-to-treat analysis [HR = 0.83 (0.60-1.15), p = 0.26]. Overall survival (OS) did not differ among these treatment arms whether analyzed on per-protocol [HR = 0.88 (0.33-2.35), p = 0.79], or by intention-to-treat [HR = 0.80 (0.48-1.32), p = 0.39] analysis. Non-relapse mortality (NRM) was significantly worse with auto-allo HCT [RR (95%CI) = 3.55 (2.17-5.80), p Conclusion Despite higher complete remission rates, there is no improvement in OS with auto-allo HCT; but this approach results in higher NRM in patients with newly diagnosed MM. At present, totality of evidence suggests that an auto-allo HCT approach for patients with newly diagnosed myeloma should not be offered outside the setting of a clinical trial.