What proportion of clinical prediction models make it to clinical practice? Protocol for a two-track follow-up study of prediction model development publications

Planned but ever published? A retrospective analysis of clinical prediction model studies registered on clinicaltrials.gov since 2000

OBJECTIVES

To describe the characteristics and publication outcomes of clinical prediction model studies registered on clinicaltrials.gov since 2000.

STUDY DESIGN AND SETTING

Observational studies registered on clinicaltrials.gov between January 1, 2000, and March 2, 2022, describing the development of a new clinical prediction model or the validation of an existing model for predicting individual-level prognostic or diagnostic risk were analyzed. Eligible clinicaltrials.gov records were classified by modeling study type (development, validation) and the model outcome being predicted (prognostic, diagnostic). Recorded characteristics included study status, sample size information, Medical Subject Headings, and plans to share individual participant data. Publication outcomes were analyzed by linking National Clinical Trial numbers for eligible records with PubMed abstracts.

RESULTS

Nine hundred twenty-eight records were analyzed from a possible 89,896 observational study records. Publications searches found 170 matching peer-reviewed publications for 137 clinicaltrials.gov records. The estimated proportion of records with 1 or more matching publications after accounting for time since study start was 2.8% at 2 years (95% CI: 1.7%, 3.9%), 12.3% at 5 years (9.8% to 14.9%) and 27% at 10 years (23% to 33%). Stratifying records by study start year indicated that publication proportions improved over time. Records tended to prioritize the development of new prediction models over the validation of existing models (76%; 704/928 vs. 24%; 182/928). At the time of download, 27% of records were marked as complete, 35% were still recruiting, and 14.7% had unknown status. Only 7.4% of records stated plans to share individual participant data.

CONCLUSION

Published clinical prediction model studies are only a fraction of overall research efforts, with many studies planned but not completed or published. Improving the uptake of study preregistration and follow-up will increase the visibility of planned research. Introducing additional registry features and guidance may improve the identification of clinical prediction model studies posted to clinical registries.

Five aspects of research waste in biomedicine: A scoping review

BACKGROUND

The number of published journal articles has grown exponentially during the last 30 years, which may have led to some wasteful research. However, the terminology associated with research waste remains unclear. To address this, we aimed to identify, define, and categorize the aspects of research waste in published biomedical reports.

METHODS

In this scoping review, we systematically searched for biomedical literature reports from 1993 to 2023 in two databases, focusing on those addressing and defining research waste. Through data charting, we analyzed and categorized the aspects of research waste.

RESULTS

Based on 4285 initial records in the searches, a total of 832 reports were included in the analysis. The included reports were primarily narrative reviews (26%) and original reports (21%). We categorized research waste into five aspects: methodological, invisible, negligible, underreported, and structural (MINUS) research waste. More than half of the reports (56%) covered methodological research waste concerning flaws in study design, study conduct, or analysis. Invisible research waste covered nonpublication, discontinuation, and lack of data-sharing. Negligible research waste primarily concerned unnecessary repetition, for example, stemming from the absence of preceding a trial with a systematic review of the literature. Underreported research waste mainly included poor reporting, resulting in a lack of transparency. Structural research waste comprised inadequate management, collaboration, prioritization, implementation, and dissemination.

CONCLUSION

MINUS encapsulates the five main aspects of research waste. Recognizing these aspects of research waste is important for addressing and preventing further research waste and thereby ensuring efficient resource allocation and scientific integrity.

How to co-design a prototype of a clinical practice tool: a framework with practical guidance and a case study

Clinical tools for use in practice-such as medicine reconciliation charts, diagnosis support tools and track-and-trigger charts-are endemic in healthcare, but relatively little attention is given to how to optimise their design. User-centred design approaches and co-design principles offer potential for improving usability and acceptability of clinical tools, but limited practical guidance is currently available. We propose a framework (FRamework for co-dESign of Clinical practice tOols or 'FRESCO') offering practical guidance based on user-centred methods and co-design principles, organised in five steps: (1) establish a multidisciplinary advisory group; (2) develop initial drafts of the prototype; (3) conduct think-aloud usability evaluations; (4) test in clinical simulations; (5) generate a final prototype informed by workshops. We applied the framework in a case study to support co-design of a prototype track-and-trigger chart for detecting and responding to possible fetal deterioration during labour. This started with establishing an advisory group of 22 members with varied expertise. Two initial draft prototypes were developed-one based on a version produced by national bodies, and the other with similar content but designed using human factors principles. Think-aloud usability evaluations of these prototypes were conducted with 15 professionals, and the findings used to inform co-design of an improved draft prototype. This was tested with 52 maternity professionals from five maternity units through clinical simulations. Analysis of these simulations and six workshops were used to co-design the final prototype to the point of readiness for large-scale testing. By codifying existing methods and principles into a single framework, FRESCO supported mobilisation of the expertise and ingenuity of diverse stakeholders to co-design a prototype track-and-trigger chart in an area of pressing service need. Subject to further evaluation, the framework has potential for application beyond the area of clinical practice in which it was applied.