The incremental value of the contribution of a biostatistician to the reporting quality in health research-A retrospective, single center, observational cohort study.

BACKGROUND The reporting quality in medical research has recently been critically discussed. While reporting guidelines intend to maximize the value from funded research, and initiatives such as the EQUATOR network have been introduced to advance high quality reporting, the uptake of the guidelines by researchers could be improved. The aim of this study was to assess the contribution of a biostatistician to the reporting and methodological quality of health research, and to identify methodological knowledge gaps. METHODS In a retrospective, single center, observational cohort study, two groups of publications were compared. The group of exposed publications had an academic biostatistician on the author list, whereas the group of non-exposed publications did not include a biostatistician of the evaluated group. Rating of reporting quality was done in blinded fashion and in duplicate. The primary outcome was a sum score based on six dimensions, ranging between 0 (worst) and 11 (best). The study protocol was reviewed and approved as a registered report. RESULTS There were 131 publications in the exposed group published between 2017 and 2018. Of these, 95 were either RCTs, observational, or prediction / prognostic studies. Corresponding matches in the group of non-exposed publications were identified in a reproducible manner. Comparison of reporting quality overall revealed a 1.60 (95%CI from 0.92 to 2.28, p <0.0001) units higher reporting quality for exposed publications. A subgroup analysis within study types showed higher reporting quality across all three study types. CONCLUSION Our study is the first to report an association of a higher reporting quality and methodological strength in health research publications with a biostatistician on the author list. The higher reporting quality persisted through subgroups of study types and dimensions. Methodological knowledge gaps were identified for prediction / prognostic studies, and for reporting on statistical methods in general and missing values, specifically

The chromosomal polymorphism of Drosophila subobscura: a microevolutionary weapon to monitor global change

The Palaearctic species Drosophila subobscura recently invaded the west coast of Chile and North America. This invasion helped to corroborate the adaptive value of the rich chromosomal polymorphism of the species, as the same clinal patterns than those observed in the original Palaearctic area were reproduced in the colonized areas in a relatively short period of time. The rapid response of this polymorphism to environmental conditions makes it a good candidate to measure the effect of the global rising of temperatures on the genetic composition of populations. Indeed, the long-term variation of this polymorphism shows a general increase in the frequency of those inversions typical of low latitudes, with a corresponding decrease of those typical of populations closer to the poles. Although the mechanisms underlying these changes are not well understood, the system remains a valid tool to monitor the genetic impact of global warming on natural populations. Heredity ( 2009) 103, 364-367; doi: 10.1038/hdy.2009.86; published online 29 July 200

The incremental value of the contribution of a biostatistician to the reporting quality in health research-A retrospective, single center, observational cohort study

BACKGROUND The reporting quality in medical research has recently been critically discussed. While reporting guidelines intend to maximize the value from funded research, and initiatives such as the EQUATOR network have been introduced to advance high quality reporting, the uptake of the guidelines by researchers could be improved. The aim of this study was to assess the contribution of a biostatistician to the reporting and methodological quality of health research, and to identify methodological knowledge gaps. METHODS In a retrospective, single center, observational cohort study, two groups of publications were compared. The group of exposed publications had an academic biostatistician on the author list, whereas the group of non-exposed publications did not include a biostatistician of the evaluated group. Rating of reporting quality was done in blinded fashion and in duplicate. The primary outcome was a sum score based on six dimensions, ranging between 0 (worst) and 11 (best). The study protocol was reviewed and approved as a registered report. RESULTS There were 131 publications in the exposed group published between 2017 and 2018. Of these, 95 were either RCTs, observational, or prediction / prognostic studies. Corresponding matches in the group of non-exposed publications were identified in a reproducible manner. Comparison of reporting quality overall revealed a 1.60 (95%CI from 0.92 to 2.28, p <0.0001) units higher reporting quality for exposed publications. A subgroup analysis within study types showed higher reporting quality across all three study types. CONCLUSION Our study is the first to report an association of a higher reporting quality and methodological strength in health research publications with a biostatistician on the author list. The higher reporting quality persisted through subgroups of study types and dimensions. Methodological knowledge gaps were identified for prediction / prognostic studies, and for reporting on statistical methods in general and missing values, specifically

The incremental value of the contribution of a biostatistician to the reporting quality in health research—A retrospective, single center, observational cohort study

Background The reporting quality in medical research has recently been critically discussed. While reporting guidelines intend to maximize the value from funded research, and initiatives such as the EQUATOR network have been introduced to advance high quality reporting, the uptake of the guidelines by researchers could be improved. The aim of this study was to assess the contribution of a biostatistician to the reporting and methodological quality of health research, and to identify methodological knowledge gaps. Methods In a retrospective, single center, observational cohort study, two groups of publications were compared. The group of exposed publications had an academic biostatistician on the author list, whereas the group of non-exposed publications did not include a biostatistician of the evaluated group. Rating of reporting quality was done in blinded fashion and in duplicate. The primary outcome was a sum score based on six dimensions, ranging between 0 (worst) and 11 (best). The study protocol was reviewed and approved as a registered report. Results There were 131 publications in the exposed group published between 2017 and 2018. Of these, 95 were either RCTs, observational, or prediction / prognostic studies. Corresponding matches in the group of non-exposed publications were identified in a reproducible manner. Comparison of reporting quality overall revealed a 1.60 (95%CI from 0.92 to 2.28, p &lt;0.0001) units higher reporting quality for exposed publications. A subgroup analysis within study types showed higher reporting quality across all three study types. Conclusion Our study is the first to report an association of a higher reporting quality and methodological strength in health research publications with a biostatistician on the author list. The higher reporting quality persisted through subgroups of study types and dimensions. Methodological knowledge gaps were identified for prediction / prognostic studies, and for reporting on statistical methods in general and missing values, specifically. </jats:sec

Questionnaire.

Questionnaires for the assessment of reporting quality. (PDF)</p

Affiliation list.

Affiliation list for control publications. (PDF)</p

Estimated between-group difference with 95%CI in the pre-specified subgroups of study type (left); raw means in exposed and non-exposed publications (right).

Unit of analysis is publication.</p

Descriptive statistics.

Descriptive statistics.</p