scholarly journals Improving anthelmintic treatment for schistosomiasis and soil-transmitted helminthiases through sharing and reuse of individual participant data

2022 ◽  
Vol 7 ◽  
pp. 5
Author(s):  
Martin Walker ◽  
Luzia T. Freitas ◽  
Julia B. Halder ◽  
Matthew Brack ◽  
Jennifer Keiser ◽  
...  
Keyword(s):  
Clinical Data ◽  
Research Agenda ◽  
Neglected Tropical Diseases ◽  
Individual Participant Data ◽  
Consultation Process ◽  
Treatment Regimens ◽  
Crucial Component ◽  
Research Themes ◽  
Individual Participant ◽  
Using Data

The Infectious Diseases Data Observatory (IDDO, https://www.iddo.org) has launched a clinical data platform for the collation, curation, standardisation and reuse of individual participant data (IPD) on treatments for two of the most globally important neglected tropical diseases (NTDs), schistosomiasis (SCH) and soil-transmitted helminthiases (STHs). This initiative aims to harness the power of data-sharing by facilitating collaborative joint analyses of pooled datasets to generate robust evidence on the efficacy and safety of anthelminthic treatment regimens. A crucial component of this endeavour has been the development of a Research Agenda to promote engagement with the SCH and STH research and disease control communities by highlighting key questions that could be tackled using data shared through the IDDO platform. Here, we give a contextual overview of the priority research themes articulated in the Research Agenda—a ‘living’ document hosted on the IDDO website—and describe the three-stage consultation process behind its development. We also discuss the sustainability and future directions of the platform, emphasising throughout the power and promise of ethical and equitable sharing and reuse of clinical data to support the elimination of NTDs.

scholarly journals Retrieval of Individual Participant Data for Exercise Meta-Analyses May Not Be Worth the Time and Effort

2016 ◽  
Vol 2016 ◽  
pp. 1-5 ◽  
Author(s):  
George A. Kelley ◽  
Kristi S. Kelley
Keyword(s):  
Logistic Regression ◽  
Rheumatic Diseases ◽  
Gold Standard ◽  
Odds Ratio ◽  
Meta Analysis ◽  
Individual Participant Data ◽  
Individual Participant ◽  
Using Data ◽  
Meta Analyses

Purpose. While individual participant data (IPD) meta-analyses are considered the gold standard for meta-analysis, the feasibility of obtaining IPD may be problematic.Methods. Using data from a previous meta-analysis of 29 studies on exercise in adults with arthritis and other rheumatic diseases, the percentage of studies in which useable IPD was provided was calculated.Results. Eight of 29 authors (28%, 95% CI = 11% to 44%) provided IPD. Using logistic regression, neither year of publication (odds ratio = 1.05, 95% CI = 0.90 to 1.27,p=0.58) nor country (odds ratio = 1.36, 95% CI = 0.20 to 10.9,p=1.00) was significantly associated with the obtainment of IPD.Conclusions. The retrieval of IPD for exercise meta-analyses may not be worth the time and effort. However, further research is needed before any final recommendations can be made.

How do academics assess the results of multiple experiments?

2018 ◽  
Author(s):  
Olmo Van den Akker ◽  
Linda Dominguez Alvarez ◽  
Marjan Bakker ◽  
Jelte M. Wicherts ◽  
Marcel A. L. M. van Assen
Keyword(s):  
Bayesian Inference ◽  
Secondary Analysis ◽  
Individual Participant Data ◽  
Additional Experiment ◽  
Underlying Theory ◽  
Individual Participant ◽  
Vote Counting

We studied how academics assess the results of a set of four experiments that all test a given theory. We found that participants’ belief in the theory increases with the number of significant results, and that direct replications were considered to be more important than conceptual replications. We found no difference between authors and reviewers in their propensity to submit or recommend to publish sets of results, but we did find that authors are generally more likely to desire an additional experiment. In a preregistered secondary analysis of individual participant data, we examined the heuristics academics use to assess the results of four experiments. Only 6 out of 312 (1.9%) participants we analyzed used the normative method of Bayesian inference, whereas the majority of participants used vote counting approaches that tend to undervalue the evidence for the underlying theory if two or more results are statistically significant.

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