Target and actual sample sizes for studies from two trial registries from 1999 to 2020: an observational study

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.

A review of sample sizes for UK pilot and feasibility studies on the ISRCTN registry from 2013 to 2020

BACKGROUND

Pilot and feasibility studies provide information to be used when planning a full trial. A sufficient sample size within the pilot/feasibility study is required so this information can be extracted with suitable precision. This work builds upon previous reviews of pilot and feasibility studies to evaluate whether the target sample size aligns with recent recommendations and whether these targets are being reached.

METHODS

A review of the ISRCTN registry was completed using the keywords "pilot" and "feasibility". The inclusion criteria were UK-based randomised interventional trials that started between 2013 (end of the previous review) and 2020. Target sample size, actual sample size and key design characteristics were extracted. Descriptive statistics were used to present sample sizes overall and by key characteristics.

RESULTS

In total, 761 studies were included in the review of which 448 (59%) were labelled feasibility studies, 244 (32%) pilot studies and 69 (9%) described as both pilot and feasibility studies. Over all included pilot and feasibility studies (n = 761), the median target sample size was 30 (IQR 20-50). This was consistent when split by those labelled as a pilot or feasibility study. Slightly larger sample sizes (median = 33, IQR 20-50) were shown for those labelled both pilot and feasibility (n = 69). Studies with a continuous outcome (n = 592) had a median target sample size of 30 (IQR 20-43) whereas, in line with recommendations, this was larger for those with binary outcomes (median = 50, IQR 25-81, n = 97). There was no descriptive difference in the target sample size based on funder type. In studies where the achieved sample size was available (n = 301), 173 (57%) did not reach their sample size target; however, the median difference between the target and actual sample sizes was small at just minus four participants (IQR -25-0).

CONCLUSIONS

Target sample sizes for pilot and feasibility studies have remained constant since the last review in 2013. Most studies in the review satisfy the earlier and more lenient recommendations however do not satisfy the most recent largest recommendation. Additionally, most studies did not reach their target sample size meaning the information collected may not be sufficient to estimate the required parameters for future definitive randomised controlled trials.

Systematic review of sample size calculations and reporting in randomized controlled trials in ophthalmology over a 20-year period

PURPOSE

Randomized Controlled Trials (RCTs) are considered the gold standard for the practice of evidence-based medicine. The purpose of this study is to systematically assess the reporting of sample size calculations in ophthalmology RCTs in 5 leading journals over a 20-year period. Reviewing sample size calculations in ophthalmology RCTs will shed light on the methodological quality of RCTs and, by extension, on the validity of published results.

METHODS

The MEDLINE database was searched to identify full reports of RCTs in the journals Ophthalmology, JAMA Ophthalmology, American Journal of Ophthalmology, Investigative Ophthalmology and Visual Science, and British Journal of Ophthalmology between January and December of the years 2000, 2010 and 2020. Screening identified 559 articles out of which 289 met the inclusion criteria for this systematic review. Data regarding sample size calculation reporting and trial characteristics was extracted for each trial by independent investigators.

RESULTS

In 2020, 77.9% of the RCTs reported sample size calculations as compared with 37% in 2000 (p < 0.001) and 60.7% in 2010 (p = 0.012). Studies reporting all necessary parameters for sample size recalculation increased significantly from 17.2% in 2000 to 39.3% in 2010 and 43.0% in 2020 (p < 0.001). Reporting of funding was greater in 2020 (98.8%) compared with 2010 (89.3%) and 2000 (53.1%). Registration in a clinical trials database occurred more frequently in 2020 (94.2%) compared to 2000 (1.2%; p < 0.001) and 2010 (68%; p < 0.001). In 2020, 38.4% of studies reported different sample sizes in the online registry from the published article. Overall, the most studied area in 2000 was glaucoma (29.6% of RCTs), whereas in 2010 and 2020, it was retina (40.2 and 37.2% of the RCTs, respectively). The number of patients enrolled in a study and the number of eyes studied was significantly greater in 2020 compared to 2000 and 2010 (p < 0.001).

CONCLUSION

Sample size calculation reporting in ophthalmology RCTs has improved significantly between the years 2000 and 2020 and is comparable to other fields in medicine. However, reporting of certain parameters remains inconsistent with current publication guidelines.

Which decentralised trial activities are reported in clinical trial protocols of drug trials initiated in 2019-2020? A cross-sectional study in ClinicalTrials.gov

OBJECTIVES

Decentralised clinical trial activities-such as participant recruitment via social media, data collection through wearables and direct-to-participant investigational medicinal product (IMP) supply-have the potential to change the way clinical trials (CTs) are conducted and with that to reduce the participation burden and improve generalisability. In this study, we investigated the decentralised and on-site conduct of trial activities as reported in CT protocols with a trial start date in 2019 or 2020.

DESIGN

We ascertained the decentralised and on-site conduct for the following operational trial activities: participant outreach, prescreening, screening, obtaining informed consent, asynchronous communication, participant training, IMP supply, IMP adherence monitoring, CT monitoring, staff training and data collection. Results were compared for the public versus private sponsors, regions involved, trial phases and four time periods (the first and second half of 2019 and 2020, respectively).

SETTING

Phases 2, 3 and 4 clinical drug trial protocols with a trial start date in 2019 or 2020 available from ClinicalTrials.gov.

OUTCOME MEASURES

The occurrence of decentralised and on-site conduct of the predefined trial activities reported in CT protocols.

RESULTS

For all trial activities, on-site conduct was more frequently reported than decentralised conduct. Decentralised conduct of the individual trial activities was reported in less than 25.6% of the 254 included protocols, except for decentralised data collection, which was reported in 68.9% of the protocols. More specifically, 81.9% of the phase 3 protocols reported decentralised data collection, compared with 73.3% and 47.0% of the phase 2 and 4 protocols, respectively. For several activities, including prescreening, screening and consenting, upward trends in reporting decentralised conduct were visible over time.

CONCLUSIONS

Decentralised methods are used in CTs, mainly for data collection, but less frequently for other activities. Sharing best practices and a detailed description in protocols can drive the adoption of decentralised methods.