Satisfaction of the uncertainty principle in cancer clinical trials: retrospective cohort analysis

The Benefits and Risks of Receiving Investigational Solid Tumor Drugs in Randomized Trials : A Systematic Review and Meta-analysis

BACKGROUND

Many patients participate in cancer trials to access new therapies. The extent to which new treatments produce clinical benefit for trial participants is unclear.

PURPOSE

To estimate the progression-free survival (PFS) and overall survival (OS) advantage of assignment to experimental groups in randomized trials for 6 solid tumors.

DATA SOURCES

ClinicalTrials.gov was searched for trials of investigational drugs with results posted between 2017 and 2021.

STUDY SELECTION

Investigational drugs were defined as those not yet having full approval from the U.S. Food and Drug Administration for the study indication. Trials were included if they were randomized and tested drugs or biologics.

DATA EXTRACTION

Data extraction was completed by 2 independent reviewers. Data were pooled using a random-effects model.

DATA SYNTHESIS

The sample included 128 trials comprising 141 comparisons of a new drug and a comparator. These comparisons included 47 050 patients. The pooled hazard ratio for PFS was 0.80 (95% CI, 0.75 to 0.85), indicating statistically significant benefit for patients in experimental groups. This corresponded to a median PFS advantage of 1.25 months (CI, 0.80 to 1.68 months). The pooled hazard ratio for OS was 0.92 (CI, 0.88 to 0.95), corresponding to a survival gain of 1.18 months (CI, 0.72 to 1.71 months). The absolute risk for a serious adverse event for comparator group patients was 29.56% (CI, 26.64% to 32.65%), with an increase in risk of 7.40% (CI, 5.66% to 9.14%) for patients in experimental groups.

LIMITATIONS

Trials in this sample were heterogeneous. Comparator group interventions were assumed to reflect standard of care.

CONCLUSION

Assignment to experimental groups produces statistically significant survival gains. However, the absolute survival gain is small, and toxicity is statistically significantly greater. The findings of this review provide reassuring evidence that patients are not meaningfully disadvantaged by assignment to comparator groups.

PRIMARY FUNDING SOURCE

Canadian Institutes of Health Research.

What do we talk about when we talk about "equipoise"? Stakeholder interviews assessing the use of equipoise in clinical research ethics

INTRODUCTION

Equipoise, generally defined as uncertainty about the relative effects of the treatments being compared in a trial, is frequently referenced as an ethical standard for the conduct of randomized clinical trials. However, it seems to be defined in several different ways and may be used differently by different individuals. We explored how clinical researchers, chairs of research ethics boards, and philosophers of science define and reason with this term.

METHODS

We completed semi-structured interviews about clinical trial ethics with 15 clinical researchers, 15 research ethics board chairs, and 15 philosophers of science/bioethicists. Each participant was asked a standardized set of 10 questions, 4 of which were specifically about equipoise. All interviews were conducted telephonically and transcribed. Responses were grouped and analysed via a modified grounded theory method.

RESULTS

Forty-three respondents defined equipoise in 7 logically distinct ways, and 2 respondents could not explicitly define it. The most common definition, offered by 14 respondents (31%), defined "equipoise" as a disagreement at the level of a community of physicians. There was significant variability in definitions offered between and within groups. When asked how they would "operationalize" equipoise - i.e. check or test for its presence - respondents provided 7 alternatives, the most common being in relation to a literature review (15/45, 33%). The vast majority of respondents (35/45, 78%) felt the concept was helpful, though many acknowledged that the lack of a clear definition or operationalization was problematic.

CONCLUSION

There is significant variation in definitions of equipoise offered by respondents, suggesting that parties within groups and between groups may be referring to different concepts when they reference "equipoise". This non-uniformity may impact fairness and transparency and opens the door to potential ethical problems in the evaluation of clinical trials - for instance, a patient may understand equipoise very differently than the researchers enrolling her in a trial, which could cause her agreement to participate to be based upon false premises.

Large Sample Size Fallacy in Trials About Antipsychotics for Neuropsychiatric Symptoms in Dementia

BACKGROUND

A typical antipsychotics for neuropsychiatric symptoms in dementia have been tested in much larger trials than the older conventional drugs. The advantage of larger sample sizes is that negative findings become less likely and the effect estimates more precise. However, as sample sizes increase, the trials also get more expensive and time consuming while exposing more patients to drugs with unknown safety profiles. Moreover, a large sample size might yield a statistically significant effect that is not necessarily clinically relevant.

OBJECTIVE

To assess (1) the variation in sample size and sample size calculations of antipsychotic trials in dementia, (2) the size of reported treatment effects and related statistical significance, and (3) general study characteristics that might be related to sample size.

STUDY DESIGN AND SETTING

We performed a meta-epidemiological study of randomized trials that tested antipsychotics for neuropsychiatric symptoms in dementia. The trials compared conventional or atypical antipsychotics with placebo or another antipsychotic. Two reviewers independently extracted sample size, sample size calculations, reported treatment effects with p-values, and general study characteristics (drug type, trial duration, type of funding). We calculated a reference sample size of 83 and 433 per study group for the placebo-controlled and head-to-head trials respectively.

RESULTS

We identified 33 placebo-controlled trials, and 18 head-to-head trials. Only 14 (42%) and 2 (11%), respectively, reported a sample size calculation. The average sample size per arm was 34 (range 6-179) in placebo-controlled trials testing conventional drugs, 107 (8-237) in such trials testing atypical drugs, and 104 (95-115) in such trials testing both drug types; it was 31 (10-88) in head-to-head trials. Thirteen out of 18 trials with sample sizes larger than required (72%) reported a statistically significant treatment effect, of which two (15%) were clinically relevant. None of the head-to-head trials reported a statistically significant treatment effect, even though some suggested non-inferiority. In placebo-controlled trials of atypical drugs, longer trial duration (>6 weeks) and commercial funding were associated with higher sample size.

CONCLUSION

Sample size calculations were poorly reported in antipsychotic trials for dementia. Placebo-controlled trials of atypical antipsychotics showed large sample size fallacy while head-to-head trials were massively underpowered.

Parents' and Adolescents' Preferences for Intensified or Reduced Treatment in Randomized Lymphoblastic Leukemia Trials

BACKGROUND

When offered participation in clinical trials, families of children with cancer face a delicate balance between cure and toxicity. Since parents and children may perceive this balance differently, this paper explores whether adolescent patients have different enrollment patterns compared to younger children in trials with different toxicity profiles.

PROCEDURE

Age-dependent participation rates in three consecutive, randomized childhood leukemia trials conducted by the Nordic Society of Paediatric Haematology and Oncology were evaluated. The ALL2000 dexamethasone/vincristine (Dx/VCR) trial tested treatment intensifications to improve cure, and the back-to-back ALL2008 6-mercaptopurine (6MP) and ALL2008 PEG-asparaginase (ASP) trials tested treatment intensifications (6MP) and toxicity reduction without compromising survival (ASP). Patient randomization and toxicity data were prospectively registered by the treating physicians.

RESULTS

Parents of young children favored treatment intensifications (Dx/VCR: 12% refusal; 6MP: 14%; ASP: 21%), whereas parents of adolescents favored treatment reductions (Dx/VCR: 52% refusal; 6MP: 30%; ASP: 8%). Adolescents were more likely to refuse intensification trials than young children (adjusted ORs 6.3; P < 0.01 [Dx/VCR] and 2.1; P = 0.04 [6MP]). Adolescents were less likely to refuse the ASP trial, with varying effect size depending on the length of the preceding consolidation treatment (adjusted OR for median consolidation length 0.15; P = 0.01). Younger children participated more frequently in only 6MP than in only ASP (14% vs. 5%), and adolescents vice versa (2% vs. 17%; P = 0.001).

CONCLUSIONS

Parents' and adolescents' divergent inclinations toward intensified or reduced therapy emphasize the necessity of actively involving adolescents in the informed consent process, which should also address motives for trial participation.

Control treatments in biologics trials of rheumatoid arthritis were often not deemed acceptable in the context of care

OBJECTIVES

Control treatments in randomized controlled trials (RCTs) should not deliberately disadvantage patients. The objectives of the study were to compare (1) willingness to include vs. (2) willingness to prescribe control treatment among physicians randomized to assess, respectively, either (1) enrollment in a trial or (2) appropriateness of control treatment in a care context for the same fictional patient.

STUDY DESIGN AND SETTING

Physicians were authors of articles about rheumatoid arthritis (RA), involved in RA patient care, and used to enrolling patients in trials. The outcomes were willingness to give control treatment: trial enrollment or control-treatment appropriateness in care context. We derived three case vignettes of fictional standard eligible patients for each of 30 RCTs assessing biologics in RA. Physicians were randomly allocated to the "trial" or "care" arm. For each of the 90 fictional patients, physicians assigned to the trial arm were asked if they would enroll the patient in the RCT the patient was derived from. For the same 90 fictional patients, physicians assigned to the care arm were asked if the control treatment of the RCT was appropriate in a context of usual care.

RESULTS

Of the 1,779 physicians invited to participate, 151 were randomized. Half of the fictional patients {41/90; 45% [95% confidence interval (CI): 37%, 53%]} would be enrolled in the RCT although the control-arm treatment of the RCT was not considered appropriate for them in the context of care. This rate differed by type of comparator [55% for non-head-to-head RCTs vs. 6% for head-to-head RCTs; adjusted odds ratio (aOR), 23.9 (95% CI: 5.5, 92.7)] and duration of trial control treatment [56% for ≤24 weeks and 15% for >24 weeks; aOR, 10.7 (95% CI: 2.8, 63.9)] but not patient RA activity [aOR, 2.5 (95% CI: 1.0, 6.6)]. The limitation of this study was that physicians gave their opinion on fictional patients with only RA.

CONCLUSIONS

Control treatments in RCTs of biologics in RA are often deemed not acceptable in the context of usual care, especially those for non-head-to-head RCTs. These findings raise ethical concerns and challenge the choice of the comparator in RCTs.

New treatments compared to established treatments in randomized trials

BACKGROUND

The proportion of proposed new treatments that are 'successful' is of ethical, scientific, and public importance. We investigated how often new, experimental treatments evaluated in randomized controlled trials (RCTs) are superior to established treatments.

OBJECTIVES

Our main question was: "On average how often are new treatments more effective, equally effective or less effective than established treatments?" Additionally, we wanted to explain the observed results, i.e. whether the observed distribution of outcomes is consistent with the 'uncertainty requirement' for enrollment in RCTs. We also investigated the effect of choice of comparator (active versus no treatment/placebo) on the observed results.

SEARCH METHODS

We searched the Cochrane Methodology Register (CMR) 2010, Issue 1 in The Cochrane Library (searched 31 March 2010); MEDLINE Ovid 1950 to March Week 2 2010 (searched 24 March 2010); and EMBASE Ovid 1980 to 2010 Week 11 (searched 24 March 2010).

SELECTION CRITERIA

Cohorts of studies were eligible for the analysis if they met all of the following criteria: (i) consecutive series of RCTs, (ii) registered at or before study onset, and (iii) compared new against established treatments in humans.

DATA COLLECTION AND ANALYSIS

RCTs from four cohorts of RCTs met all inclusion criteria and provided data from 743 RCTs involving 297,744 patients. All four cohorts consisted of publicly funded trials. Two cohorts involved evaluations of new treatments in cancer, one in neurological disorders, and one for mixed types of diseases. We employed kernel density estimation, meta-analysis and meta-regression to assess the probability of new treatments being superior to established treatments in their effect on primary outcomes and overall survival.

MAIN RESULTS

The distribution of effects seen was generally symmetrical in the size of difference between new versus established treatments. Meta-analytic pooling indicated that, on average, new treatments were slightly more favorable both in terms of their effect on reducing the primary outcomes (hazard ratio (HR)/odds ratio (OR) 0.91, 99% confidence interval (CI) 0.88 to 0.95) and improving overall survival (HR 0.95, 99% CI 0.92 to 0.98). No heterogeneity was observed in the analysis based on primary outcomes or overall survival (I(2) = 0%). Kernel density analysis was consistent with the meta-analysis, but showed a fairly symmetrical distribution of new versus established treatments indicating unpredictability in the results. This was consistent with the interpretation that new treatments are only slightly superior to established treatments when tested in RCTs. Additionally, meta-regression demonstrated that results have remained stable over time and that the success rate of new treatments has not changed over the last half century of clinical trials. The results were not significantly affected by the choice of comparator (active versus placebo/no therapy).

AUTHORS' CONCLUSIONS

Society can expect that slightly more than half of new experimental treatments will prove to be better than established treatments when tested in RCTs, but few will be substantially better. This is an important finding for patients (as they contemplate participation in RCTs), researchers (as they plan design of the new trials), and funders (as they assess the 'return on investment'). Although we provide the current best evidence on the question of expected 'success rate' of new versus established treatments consistent with a priori theoretical predictions reflective of 'uncertainty or equipoise hypothesis', it should be noted that our sample represents less than 1% of all available randomized trials; therefore, one should exercise the appropriate caution in interpretation of our findings. In addition, our conclusion applies to publicly funded trials only, as we did not include studies funded by commercial sponsors in our analysis.

Treatment success in pragmatic randomised controlled trials: a review of trials funded by the UK Health Technology Assessment programme

BACKGROUND

Previous research reviewed treatment success and whether the collective uncertainty principle is met in RCTs in the US National Cancer Institute portfolio. This paper classifies clinical trials funded by the UK HTA programme by results using the method applied to the US Cancer Institute trials, and compares the two portfolios.

METHODS

Data on all completed randomised controlled trials funded by the HTA programme 1993-2008 were extracted. Each trial's primary results was classified into six categories; 1) statistically significant in favour of the new treatment, 2) statistically significant in favour of the control treatment 3) true negative, 4) truly inconclusive, 5) inconclusive in favour of new treatment or 6) inconclusive in favour of control treatment. Trials were classified by comparing the 95% confidence interval for the difference in primary outcome to the difference specified in the sample size calculation. The results were compared with Djulbegovic's analysis of NCI trials.

RESULTS

Data from 51 superiority trials were included, involving over 48,000 participants and a range of diseases and interventions. 85 primary comparisons were available because some trials had more than two randomised arms or had several primary outcomes. The new treatment had superior results (whether significant or not) in 61% of the comparisons (52/85 95% CI 49.9% to 71.6%). The results were conclusive in 46% of the comparisons (19% statistically significant in favour of the new treatment, 5% statistically significant in favour of the control and 22% true negative). The results were classified as truly inconclusive (i.e. failed to answer the question asked) for 24% of comparisons (20/85). HTA trials included fewer truly inconclusive and statistically significant results and more results rated as true negative than NCI trials.

CONCLUSIONS

The pattern of results in HTA trials is similar to that of the National Cancer Institute portfolio. Differences that existed were plausible given the differences in the types of trials -HTA trials are more pragmatic. The results indicate HTA trials are compatible with equipoise. This classification usefully summarises the results from clinical trials and enables comparisons of different portfolios of trials.

The paradox of equipoise: the principle that drives and limits therapeutic discoveries in clinical research

BACKGROUND

Progress in clinical medicine relies on the willingness of patients to take part in experimental clinical trials, particularly randomized controlled trials (RCTs). Before agreeing to enroll in clinical trials, patients require guarantees that they will not knowingly be harmed and will have the best possible chances of receiving the most favorable treatments. This guarantee is provided by the acknowledgment of uncertainty (equipoise), which removes ethical dilemmas and makes it easier for patients to enroll in clinical trials.

METHODS

Since the design of clinical trials is mostly affected by clinical equipoise, the "clinical equipoise hypothesis" has been postulated. If the uncertainty requirement holds, this means that investigators cannot predict what they are going to discover in any individual trial that they undertake. In some instances, new treatments will be superior to standard treatments, while in others, standard treatments will be superior to experimental treatments, and in still others, no difference will be detected between new and standard treatments. It is hypothesized that there must be a relationship between the overall pattern of treatment successes and the uncertainties that RCTs are designed to address.

RESULTS

An analysis of published trials shows that the results cannot be predicted at the level of individual trials. However, the results also indicate that the overall pattern of discovery of treatment success across a series of trials is predictable and is consistent with clinical equipoise hypothesis. The analysis shows that we can discover no more than 25% to 50% of successful treatments when they are tested in RCTs. The analysis also indicates that this discovery rate is optimal in helping to preserve the clinical trial system; a high discovery rate (eg, a 90% to 100% probability of success) is neither feasible nor desirable since under these circumstances, neither the patient nor the researcher has an interest in randomization. This in turn would halt the RCT system as we know it.

CONCLUSIONS

The "principle or law of clinical discovery" described herein predicts the efficiency of the current system of RCTs at generating discoveries of new treatments. The principle is derived from the requirement for uncertainty or equipoise as a precondition for RCTs, the precept that paradoxically drives discoveries of new treatments while limiting the proportion and rate of new therapeutic discoveries.

Stopping randomized trials early for benefit: a protocol of the Study Of Trial Policy Of Interim Truncation-2 (STOPIT-2)

Background

Randomized clinical trials (RCTs) stopped early for benefit often receive great attention and affect clinical practice, but pose interpretational challenges for clinicians, researchers, and policy makers. Because the decision to stop the trial may arise from catching the treatment effect at a random high, truncated RCTs (tRCTs) may overestimate the true treatment effect. The Study Of Trial Policy Of Interim Truncation (STOPIT-1), which systematically reviewed the epidemiology and reporting quality of tRCTs, found that such trials are becoming more common, but that reporting of stopping rules and decisions were often deficient. Most importantly, treatment effects were often implausibly large and inversely related to the number of the events accrued. The aim of STOPIT-2 is to determine the magnitude and determinants of possible bias introduced by stopping RCTs early for benefit.

Methods/Design

We will use sensitive strategies to search for systematic reviews addressing the same clinical question as each of the tRCTs identified in STOPIT-1 and in a subsequent literature search. We will check all RCTs included in each systematic review to determine their similarity to the index tRCT in terms of participants, interventions, and outcome definition, and conduct new meta-analyses addressing the outcome that led to early termination of the tRCT. For each pair of tRCT and systematic review of corresponding non-tRCTs we will estimate the ratio of relative risks, and hence estimate the degree of bias. We will use hierarchical multivariable regression to determine the factors associated with the magnitude of this ratio. Factors explored will include the presence and quality of a stopping rule, the methodological quality of the trials, and the number of total events that had occurred at the time of truncation.

Finally, we will evaluate whether Bayesian methods using conservative informative priors to "regress to the mean" overoptimistic tRCTs can correct observed biases.

Discussion

A better understanding of the extent to which tRCTs exaggerate treatment effects and of the factors associated with the magnitude of this bias can optimize trial design and data monitoring charters, and may aid in the interpretation of the results from trials stopped early for benefit.

Treatment success in cancer: new cancer treatment successes identified in phase 3 randomized controlled trials conducted by the National Cancer Institute-sponsored cooperative oncology groups, 1955 to 2006

BACKGROUND

The evaluation of research output, such as estimation of the proportion of treatment successes, is of ethical, scientific, and public importance but has rarely been evaluated systematically. We assessed how often experimental cancer treatments that undergo testing in randomized clinical trials (RCTs) result in discovery of successful new interventions.

METHODS

We extracted data from all completed (published and unpublished) phase 3 RCTs conducted by the National Cancer Institute cooperative groups since their inception in 1955. Therapeutic successes were determined by (1) assessing the proportion of statistically significant trials favoring new or standard treatments, (2) determining the proportion of the trials in which new treatments were considered superior to standard treatments according to the original researchers, and (3) quantitatively synthesizing data for main clinical outcomes (overall and event-free survival).

RESULTS

Data from 624 trials (781 randomized comparisons) involving 216 451 patients were analyzed. In all, 30% of trials had statistically significant results, of which new interventions were superior to established treatments in 80% of trials. The original researchers judged that the risk-benefit profile favored new treatments in 41% of comparisons (316 of 766). Hazard ratios for overall and event-free survival, available for 614 comparisons, were 0.95 (99% confidence interval [CI], 0.93-0.98) and 0.90 (99% CI, 0.87- 0.93), respectively, slightly favoring new treatments. Breakthrough interventions were discovered in 15% of trials.

CONCLUSIONS

Approximately 25% to 50% of new cancer treatments that reach the stage of assessment in RCTs will prove successful. The pattern of successes has become more stable over time. The results are consistent with the hypothesis that the ethical principle of equipoise defines limits of discoverability in clinical research and ultimately drives therapeutic advances in clinical medicine.

Statistical Power of Negative Randomized Controlled Trials Presented at American Society for Clinical Oncology Annual Meetings

Purpose

To investigate the prevalence of underpowered randomized controlled trials (RCTs) presented at American Society of Clinical Oncology (ASCO) annual meetings.

Methods

We surveyed all two-arm phase III RCTs presented at ASCO annual meetings from 1995 to 2003 for which negative results were obtained. Post hoc calculations were performed using a power of 80% and an α level of .05 (two sided) to determine sample sizes required to detect small, medium, and large effect sizes. For studies reporting a proportion or time-to-event as primary end point, effect size was expressed as an odds ratio (OR) or hazard ratio (HR), respectively, with a small effect size defined as OR/HR ≥ 1.3, medium effect size defined as OR/HR ≥ 1.5, and large effect size defined as OR/HR ≥ 2.0. Logistic regression was used to identify factors associated with lack of statistical power.

Results

Of 423 negative RCTs for which post hoc sample size calculations could be performed, 45 (10.6%), 138 (32.6%), and 233 (55.1%) had adequate sample size to detect small, medium, and large effect sizes, respectively. Only 35 negative RCTs (7.1%) reported a reason for inadequate sample size. In a multivariable model, studies that were presented at oral sessions (P = .0038), multicenter studies supported by a cooperative group (P < .0001), and studies with time to event as primary outcome (P < .0001) were more likely to have adequate sample size.

Conclusion

More than half of negative RCTs presented at ASCO annual meetings do not have an adequate sample to detect a medium-size treatment effect.

A questionnaire survey of current UK practice for adjuvant radiotherapy following surgery for oral and oropharyngeal squamous cell carcinoma

A postal questionnaire was sent to 281 members of the British Association of Head and Neck Oncologists (BAHNO) to survey, which patients should receive adjuvant radiotherapy following primary surgery for oral and oropharyngeal squamous cell carcinoma (O&OSCC). Two hundred and one clinicians were involved in decision making for adjuvant radiotherapy in O&OSCC, of which, 132 (66%) responded. Apart from general agreement that patients with involved margins or extracapsular spread (ECS) should have adjuvant radiotherapy and that in patients with small tumours with clear margins and no neck metastasis, radiotherapy should be avoided, opinion was divided. Considerable variation in opinion in the UK was identified for a subgroup of intermediate risk patients as to whether they should have adjuvant radiotherapy. The majority of respondents (95%) would consider submitting patients to a prospective multi-centre trial. There is a need for research regarding adjuvant radiotherapy for O&OSCC patients at intermediate risk of relapse following primary surgery.

Bias in clinical intervention research

Research on bias in clinical trials may help identify some of the reasons why investigators sometimes reach the wrong conclusions about intervention effects. Several quality components for the assessment of bias control have been suggested, but although they seem intrinsically valid, empirical evidence is needed to evaluate their effects on the extent and direction of bias. This narrative review summarizes the findings of methodological studies on the influence of bias in clinical trials. A number of methodological studies suggest that lack of adequate randomization in published trial reports may be associated with more positive estimates of intervention effects. The influence of double-blinding and follow-up is less clear. Several studies have found a significant association between funding sources and pro-industry conclusions. However, the methodological studies also show that bias is difficult to detect and appraise. The extent of bias in individual trials is unpredictable. A-priori exclusion of trials with certain characteristics is not recommended. Appraising bias control in individual trials is necessary to avoid making incorrect conclusions about intervention effects.

Are experimental treatments for cancer in children superior to established treatments? Observational study of randomised controlled trials by the Children's Oncology Group

OBJECTIVES

To assess how often new treatments for childhood cancer assessed in phase III randomised trials are superior or inferior to standard treatments and whether the pattern of successes and failures in new treatments is consistent with uncertainty being the ethical basis for enrolling patients in such trials.

DESIGN

Observational study.

SETTING

Phase III randomised controlled trials carried out under the aegis of the Children's Oncology Group between 1955 and 1997, regardless of whether they were published.

MAIN OUTCOME MEASURES

Overall survival, event free survival, and treatment related mortality.

RESULTS

126 trials were included, involving 152 comparisons and 36,567 patients. The odds ratio for overall survival with experimental treatments was 0.96 (99% confidence interval 0.89 to 1.03), indicating that new treatments are as likely to be inferior as they are to be superior to standard treatments. This result was not affected by publication bias, methodological quality, treatment type, disease, or comparator.

CONCLUSIONS

New treatments in childhood cancer tested in randomised controlled trials are, on average, as likely to be inferior as they are to be superior to standard treatments, confirming that the uncertainty principle has been operating.

Sobre cómo analizar la credibilidad de un ensayo clínico o metaanálisis cuyo resultado principal se ofrezca en odds ratio, riesgo relativo o hazard ratio

Beyond the type of design or the statistical analysis applied, the credibility of a research study lies in the compatibility of its results with the intensity that the reader could accept that the phenomenon studied might have from a biological point of view. Ultimately this requires a value judgment. The present article describes a procedure that can be used to objectively approach the limits of intensity that that a biological phenomenon could have, according to the data presented, so that, based on the reader's judgment derived from the available knowledge of the problem, the study can be deemed credible. The procedure is valid when the results of the study are expressed in odds ratio, relative risk or hazard ratio. Although these statistics are difficult to interpret, they are probably the most widely used in clinical trials and meta-analyses, that is, in studies whose methodological designs provide the highest level of evidence.