Assessing risk of bias: a proposal for a unified framework for observational studies and randomized trials

Preventable sources of bias in subgroup analyses and secondary outcomes of randomized trials

BACKGROUND

Randomized controlled trials are the gold standard for determining treatment efficacy in medicine. To deter harmful practices such as p-hacking and hypothesizing after the results are known, any analysis of subgroups and secondary outcomes must be documented and pre-specified. However, they can still introduce bias (and routinely do) if they are not treated with the same consideration as the primary analysis.

METHODS

We describe several sources of bias that affect subgroup and secondary outcome analyses using published randomized trials and causal directed acyclic graphs (DAGs).

RESULTS

We use the RECOVERY and START trials to elucidate sources of bias in analyses of subgroups and secondary outcomes. Chance imbalance can occur if the distribution of prognostic variables is not sought for any given subgroup analysis as for the main analysis. This differential distribution of prognostic variables can also occur in analyses of secondary outcomes. Selection bias can occur if the subgroup variable is causally related to staying in the trial. Given loss to follow up is not normally addressed in subgroups, attrition bias can pass unnoticed in these cases. In every case, the solution is to take the same considerations for these analyses as we do for primary analyses.

CONCLUSIONS

Approval of treatments and clinical decisions can occur based on results from subgroup or secondary outcome analyses. Thus, it is important to give them the same treatment as primary analyses to avoid preventable biases.

Comorbidities of deformational plagiocephaly in infancy: A scoping review

AIM

While deformational plagiocephaly (DP) is suspected to be associated with comorbidities, their nature and prevalence are unclear. This scoping review aims to report DP comorbidities occurring until the age of 2 years, their prevalence and whether they depend on the child's age and sex.

METHODS

Relevant studies were identified by searching the Cochrane, MEDLINE, EMBASE, PubMed and EBSCO databases from 1992 to 30 April 2021. Data on study characteristics, comorbidities and assessment instruments were extracted and qualitatively synthesised. Risk of bias was assessed and studies with high risk of bias were excluded.

RESULTS

Studies meeting selection criteria (n = 27) often evaluated groups from tertiary clinics, implying selection bias. Studies reported on developmental delay (n = 16), limited speech production (n = 1), auditory (n = 3), visual (n = 3), mandibular (n = 3) and neurological impairments (n = 1). The data did not allow prevalence calculation or modifying effect of sex. Due to biased data, the review provided no evidence on DP comorbidities. Weak evidence suggested that in the selective samples, DP was associated with motor and language delays in the first year.

CONCLUSION

Due to biased data, no evidence on comorbidity in infants with DP was available. Our study underlined the need of risk of bias assessment in scoping reviews.

Time to level up: A systematic review of interventions aiming to reduce stigma toward autistic people

LAY ABSTRACT

How non-autistic people think about autistic people impacts autistic people negatively. Many studies developed trainings to reduce autism stigma. The existing trainings vary a lot in terms of study design, content, and reported effectiveness. This means that a review studying how the studies have been conducted is needed. We also looked at the quality of these studies. We collected and studied 26 studies that tried to reduce stigma toward autistic people. The studies often targeted White K-12 students and college students. Most trainings were implemented once. Trainings frequently used video or computer. Especially, recent studies tended to use online platforms. The study quality was poor for most studies. Some studies made inaccurate claims about the intervention effectiveness. Studies did not sufficiently address study limitations. Future trainings should aim to figure out why and how interventions work. How intervention changes people's behavior and thoughts should be studied. Researchers should study whether the training can change the societal stigma. Also, researchers should use a better study design.

Common tool structures and approaches to risk of bias assessment: implications for systematic reviewers

There are numerous tools available to assess the risk of bias in individual studies in a systematic review. These tools have different structures, including scales and checklists, which may or may not separate their items by domains. There are also various approaches and guides for the process, scoring, and interpretation of risk of bias assessments, such as value judgments, quality scores, and relative ranks. The objective of this commentary, which is part of the JBI Series on Risk of Bias, is to discuss some of the distinctions among different tool structures and approaches to risk of bias assessment and the implications of these approaches for systematic reviewers.