Outcome reporting bias in observational epidemiology studies on phthalates

Air pollution and risk of 32 health conditions: outcome-wide analyses in a population-based prospective cohort in Southwest China

BACKGROUND

Uncertainty remains about the long-term effects of air pollutants (AP) on multiple diseases, especially subtypes of cardiovascular disease (CVD). We aimed to assess the individual and joint associations of fine particulate matter (PM2.5), along with its chemical components, nitrogen dioxide (NO2) and ozone (O3), with risks of 32 health conditions.

METHODS

A total of 17,566 participants in Sichuan Province, China, were included in 2018 and followed until 2022, with an average follow-up period of 4.2 years. The concentrations of AP were measured using a machine-learning approach. The Cox proportional hazards model and quantile g-computation were applied to assess the associations between AP and CVD.

RESULTS

Per interquartile range (IQR) increase in PM2.5 mass, NO2, O3, nitrate, ammonium, organic matter (OM), black carbon (BC), chloride, and sulfate were significantly associated with increased risks of various conditions, with hazard ratios (HRs) ranging from 1.06 to 2.48. Exposure to multiple air pollutants was associated with total cardiovascular disease (HR 1.75, 95% confidence intervals (CIs) 1.62-1.89), hypertensive diseases (1.49, 1.38-1.62), cardiac arrests (1.52, 1.30-1.77), arrhythmia (1.76, 1.44-2.15), cerebrovascular diseases (1.86, 1.65-2.10), stroke (1.77, 1.54-2.03), ischemic stroke (1.85, 1.61-2.12), atherosclerosis (1.77, 1.57-1.99), diseases of veins, lymphatic vessels, and lymph nodes (1.32, 1.15-1.51), pneumonia (1.37, 1.16-1.61), inflammatory bowel diseases (1.34, 1.16-1.55), liver diseases (1.59, 1.43-1.77), type 2 diabetes (1.48, 1.26-1.73), lipoprotein metabolism disorders (2.20, 1.96-2.47), purine metabolism disorders (1.61, 1.38-1.88), anemia (1.29, 1.15-1.45), sleep disorders (1.54, 1.33-1.78), renal failure (1.44, 1.21-1.72), kidney stone (1.27, 1.13-1.43), osteoarthritis (2.18, 2.00-2.39), osteoporosis (1.36, 1.14-1.61). OM had max weights for joint effects of AP on many conditions.

CONCLUSIONS

Long-term exposure to increased levels of multiple air pollutants was associated with risks of multiple health conditions. OM accounted for substantial weight for these increased risks, suggesting it may play an important role in these associations.

Citation bias and other determinants of citation in biomedical research: findings from six citation networks

OBJECTIVES

When the probability of being cited depends on the outcome of that study, this is called citation bias. The aim of this study is to assess the determinants of citation and how these compare across six different biomedical research fields.

STUDY DESIGN AND SETTING

Citation network analyses were performed for six biomedical research questions. After identifying all relevant publications, all potential citations were mapped together with the actually performed citations in each network. As determinants of citation we assessed the following: study outcome, study design, sample size, journal impact factor, gender, affiliation, authority and continent of the corresponding author, funding source, title of the publication, number of references, and self-citation. Random effect logistic regression analysis was used to assess these factors.

RESULTS

Four out of six networks showed evidence for citation bias. Self-citation, authority of the author, and journal impact factor were also positively associated with the probability of citation in all networks.

CONCLUSION

The probability of being cited seems associated with positive study outcomes, the authority of its authors, and the journal in which that article is published. In addition, each network showed specific characteristics that impact the citation dynamics and that need to be considered when performing and interpreting citation analyses.

Determinants of Citation in Epidemiological Studies on Phthalates: A Citation Analysis

Citing of previous publications is an important factor in knowledge development. Because of the great amount of publications available, only a selection of studies gets cited, for varying reasons. If the selection of citations is associated with study outcome this is called citation bias. We will study determinants of citation in a broader sense, including e.g. study design, journal impact factor or the funding source of the publication. As a case study we assess which factors drive citation in the human literature on phthalates, specifically the metabolite mono(2-ethylhexyl) phthalate (MEHP). A systematic literature search identified all relevant publications on human health effect of MEHP. Data on potential determinants of citation were extracted in duplo. Specialized software was used to create a citation network, including all potential citation pathways. Random effect logistic regression was used to assess whether these determinants influence the likelihood of citation. 112 Publications on MEHP were identified, with 5684 potential citation pathways of which 551 were actual citations. Reporting of a harmful point estimate, journal impact factor, authority of the author, a male corresponding author, research performed in North America and self-citation were positively associated with the likelihood of being cited. In the literature on MEHP, citation is mostly driven by a number of factors that are not related to study outcome. Although the identified determinants do not necessarily give strong indications of bias, it shows selective use of published literature for a variety of reasons.

Publication and related biases in health services research: a systematic review of empirical evidence

Background

Publication and related biases (including publication bias, time-lag bias, outcome reporting bias and p-hacking) have been well documented in clinical research, but relatively little is known about their presence and extent in health services research (HSR). This paper aims to systematically review evidence concerning publication and related bias in quantitative HSR.

Methods

Databases including MEDLINE, EMBASE, HMIC, CINAHL, Web of Science, Health Systems Evidence, Cochrane EPOC Review Group and several websites were searched to July 2018. Information was obtained from: (1) Methodological studies that set out to investigate publication and related biases in HSR; (2) Systematic reviews of HSR topics which examined such biases as part of the review process. Relevant information was extracted from included studies by one reviewer and checked by another. Studies were appraised according to commonly accepted scientific principles due to lack of suitable checklists. Data were synthesised narratively.

Results

After screening 6155 citations, four methodological studies investigating publication bias in HSR and 184 systematic reviews of HSR topics (including three comparing published with unpublished evidence) were examined. Evidence suggestive of publication bias was reported in some of the methodological studies, but evidence presented was very weak, limited in both quality and scope. Reliable data on outcome reporting bias and p-hacking were scant. HSR systematic reviews in which published literature was compared with unpublished evidence found significant differences in the estimated intervention effects or association in some but not all cases.

Conclusions

Methodological research on publication and related biases in HSR is sparse. Evidence from available literature suggests that such biases may exist in HSR but their scale and impact are difficult to estimate for various reasons discussed in this paper.

Systematic review registration

PROSPERO 2016 CRD42016052333.

Comparisons between protocols and publications of case-control studies: analysis of potential causes of non-reproducibility and recommendations for enhancing the quality of personalization in healthcare

Background

Selective reporting of results in published case-control studies has been widely suspected, but little comprehensive information on selective reporting is available with regard to case-control studies. We aimed to evaluate the concordance of findings between publications and the protocols of case-control studies and to assess the level of selective reporting of results in case-control studies.

Methods

The databases of Embase, Medline, Scopus, and Web of Science were searched to identify case-control study protocols published between January 1, 1990 and December 31, 2017. The numbers and characteristics of predefined exposures (or factors) were extracted from the protocols. The reported and unreported factors were both collected from the published studies and protocols. The frequency of selective reporting of results were estimated by identifying the discrepancies of factors between the protocols and the published studies. Study sample size and the extent of selective reporting of factors were measured by a Spearman correlation analysis.

Results

Fourteen protocols with 24 published studies and 159 factors were identified, of which eight protocols (57.1%) had discrepancies between the publications and protocols. The prevalence of incomplete reporting in published case-control studies was 42.9% (6/14), with participant characteristics, anthropometric and laboratory measurement variables more likely to be unreported. A total of 16,835 cases and 56,049 controls were recruited in the 14 protocols of case-control studies (sample size ranges from 428 to 52,596 per study). Sample size had no statistical significance with selective reporting of results (P > 0.05).

Conclusion

The study protocols should be publicly available prior to the completion of case-control studies so that the potential bias can be assessed by the readers. Our findings highlight the need for investigators, peer reviewers, and readers to exercise increased awareness and scrutiny due to the undesirable practice of selective reporting of results in medical sciences causing the loss of potentially important information, thus impacting quality of personalized attitude in healthcare in the context of the predictive, preventive, and personalized medicine.