A systematic review of how missing data are handled and reported in <scp>multi‐database</scp> pharmacoepidemiologic studies

Hunt, Nicholas B; Gardarsdóttir, Helga; Bazelier, Marloes T; Klungel, Olaf H.; Pajouheshnia, Romin

doi:10.1002/pds.5245

Cited by 14 publications

(11 citation statements)

References 32 publications

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“…We observed this most often in the assessment of bias due to missing data. This poor reporting is not specific to COVID‐19 research and has also been observed for pharmacoepidemiologic studies in general 30,31 . Understandably, due to word limits, authors are unable to elaborate on all methodological decisions in their manuscript.…”

Section: Discussionmentioning

confidence: 99%

“…This poor reporting is not specific to COVID-19 research and has also been observed for pharmacoepidemiologic studies in general. 30,31 Understandably, due to word limits, authors are unable to elaborate on all methodological decisions in their manuscript. However, in situations where methods deviate from generally accepted methods, substantiation of choices that were made is needed for correct interpretation of the results of a study as well as for assessment of its validity.…”

Section: Summary Of Findingsmentioning

confidence: 99%

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Bias in observational studies on the effectiveness of in hospital use of hydroxychloroquine in COVID‐19

Hempenius

Bots

Groenwold

et al. 2023

Pharmacoepidemiology and Drug

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Purpose During the first waves of the coronavirus pandemic, evidence on potential effective treatments was urgently needed. Results from observational studies on the effectiveness of hydroxychloroquine (HCQ) were conflicting, potentially due to biases. We aimed to assess the quality of observational studies on HCQ and its relation to effect sizes. Methods PubMed was searched on 15 March 2021 for observational studies on the effectiveness of in‐hospital use of HCQ in COVID‐19 patients, published between 01/01/2020 and 01/03/2021 on. Study quality was assessed using the ROBINS‐I tool. Association between study quality and study characteristics (journal ranking, publication date, and time between submission and publication) and differences between effects sizes found in observational studies compared to those found in RCTs, were assessed using Spearman's correlation. Results Eighteen of the 33 (55%) included observational studies were scored as critical risk of bias, eleven (33%) as serious risk and only four (12%) as moderate risk of bias. Biases were most often scored as critical in the domains related to selection of participants (n = 13, 39%) and bias due to confounding (n = 8, 24%). There were no significant associations found between the study quality and the characteristics nor between the study quality and the effect estimates. Discussion Overall, the quality of observational HCQ studies was heterogeneous. Synthesis of evidence of effectiveness of HCQ in COVID‐19 should focus on RCTs and carefully consider the added value and quality of observational evidence.

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Section: Discussionmentioning

confidence: 99%

Section: Summary Of Findingsmentioning

confidence: 99%

Bias in observational studies on the effectiveness of in hospital use of hydroxychloroquine in COVID‐19

Hempenius

Bots

Groenwold

et al. 2023

Pharmacoepidemiology and Drug

Self Cite

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“…For the use of real‐world evidence (RWE) in the regulatory realm, both the US Food and Drug Administration and the European Medicines Agency have pointed out the challenges posed by missing data, recommending a series of approaches based on methods such as inverse probability weighting or likelihood‐based methods 21 as well as multiple imputation approaches, 22 given full transparency regarding the assumptions required for validity of these methods, 23‐28 and accompanied by sensitivity analyses 25 . Recent literature has noted that few studies address how missingness assumptions are actually checked, or how the missingness is handled in analyses; studies that propose recommendations do so in a non‐systematic fashion 12,19,29,30,31,32,33 . Our workflow is an easy‐to‐implement approach to check analytical assumptions around the potential mechanisms of missingness of critical variables before conducting further downstream analyses.…”

Section: Discussionmentioning

confidence: 99%

A systematic approach towards missing lab data in electronic health records: A case study in non‐small cell lung cancer and multiple myeloma

Sondhi

Weberpals

Yerram

et al. 2023

CPT Pharmacom & Syst Pharma

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Real‐world data derived from electronic health records often exhibit high levels of missingness in variables, such as laboratory results, presenting a challenge for statistical analyses. We developed a systematic workflow for gathering evidence of different missingness mechanisms and performing subsequent statistical analyses. We quantify evidence for missing completely at random (MCAR) or missing at random (MAR), mechanisms using Hotelling's multivariate t‐test, and random forest classifiers, respectively. We further illustrate how to apply sensitivity analyses using the not at random fully conditional specification procedure to examine changes in parameter estimates under missing not at random (MNAR) mechanisms. In simulation studies, we validated these diagnostics and compared analytic bias under different mechanisms. To demonstrate the application of this workflow, we applied it to two exemplary case studies with an advanced non‐small cell lung cancer and a multiple myeloma cohort derived from a real‐world oncology database. Here, we found strong evidence against MCAR, and some evidence of MAR, implying that imputation approaches that attempt to predict missing values by fitting a model to observed data may be suitable for use. Sensitivity analyses did not suggest meaningful departures of our analytic results under potential MNAR mechanisms; these results were also in line with results reported in clinical trials.

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“…Although complete case analysis is often used in medical studies [25] it has its limits, especially when the reason for dropouts is not known [26]. For the necessary randomized trial measures to prevent dropouts like reminders and recruitment via medical personnel should be implemented as well as investigations concerning the dropout reason.…”

Section: Discussionmentioning

confidence: 99%

Observational study on the influence of an app-based self-management program on the quality of life of women with endometriosis.

Rohloff¹,

Rothenhöfer²,

Götz³

et al. 2022

Preprint

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Purpose: Endometriosis can significantly impair the quality of life of those affected. Multimodal self-help measures are recommended but often difficult to access. Smartphone apps have been shown to improve quality of life for other conditions with chronic pain. The aim of this study was to examine whether there is evidence of beneficial effects of the smartphone app “Endo-App®” and whether a multicenter randomized controlled trial should be planned to substantiate these effects. Methods: In a sample of N=106 women affected by endometriosis the present study determined the influence of the use of Endo-App ® on their quality of life. Among others, the validated questionnaire Endometriosis Health Profile from Oxford University was used for this purpose. Results: The use of Endo-App ® lead to a highly significant improvement in quality of life already after two weeks. A statistically significant change was found for nine out of ten measured variables of quality of life. A series of further analyses validated that the measured positive effects were not due to other confounding factors. Conclusion: In summary, the results indicate that the quality of life of women with endometriosis improved by the digital self-management tool Endo-App ®. More studies are needed to further explore the influence of the app on quality of life and as confirmatory evidence of beneficial effects. For this purpose, a randomized controlled trial should be conducted over a longer period of time. Trial registration: This trial is registered at clinicaltrials.gov under the registration number NCT05528601 on August 18, 2022. It was retrospectively registered.

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A systematic review of how missing data are handled and reported in multi‐database pharmacoepidemiologic studies

Cited by 14 publications

References 32 publications

Bias in observational studies on the effectiveness of in hospital use of hydroxychloroquine in COVID‐19

Bias in observational studies on the effectiveness of in hospital use of hydroxychloroquine in COVID‐19

A systematic approach towards missing lab data in electronic health records: A case study in non‐small cell lung cancer and multiple myeloma

Observational study on the influence of an app-based self-management program on the quality of life of women with endometriosis.

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