Feasibility and acceptability of conducting a randomized clinical trial designed to improve interpretation of screening mammography

Reporting of Participant Demographics in Clinical Trials Published in General Radiology Journals

OBJECTIVES

The reporting of research participant demographics provides insights into study generalizability. Our study aimed to determine the frequency at which participant age, sex/gender, race/ethnicity, and socioeconomic status (SES) are reported and used for subgroup analyses in radiology randomized controlled trials (RCTs) and their secondary analyses; as well as the study characteristics associated with, and the classification systems used for demographics reporting.

METHODS

RCTs and their secondary analyses published in 8 leading radiology journals between 2013 and 2021 were included. Associations between study characteristics and demographic reporting were tested with the chi-square goodness of fit test for categorical variables, Wilcoxon-Mann-Whitney test for impact factor, and logistic regression for publication year.

RESULTS

Among 432 included articles, 89.4% (386) reported age, 90.3% (390) sex/gender, 5.6% (24) race/ethnicity, and 3.0% (13) SES. Among articles that reported these demographics and were not specific to a subgroup, results were analyzed by age in 14.2% (55/386), sex/gender in 19.4% (66/340), race/ethnicity in 13.6% (3/22), and SES in 46.2% (6/13). Journal, impact factor, and last author continent were predictors of race/ethnicity and SES reporting. Funding was associated with race/ethnicity reporting. No study reported sex and gender separately, or documented transgender, nonbinary gender spectrum or intersex participants. A single category for race/ethnicity was used in 37.5% (9/24) of studies, consisting of either "White" or "Caucasian."

CONCLUSION

The reporting of participant demographics in radiology trials is variable and not always representative of the population diversity. Editorial guidelines on the reporting and analysis of participant demographics could help standardize practices.

Collective intelligence meets medical decision-making: the collective outperforms the best radiologist

While collective intelligence (CI) is a powerful approach to increase decision accuracy, few attempts have been made to unlock its potential in medical decision-making. Here we investigated the performance of three well-known collective intelligence rules (“majority”, “quorum”, and “weighted quorum”) when applied to mammography screening. For any particular mammogram, these rules aggregate the independent assessments of multiple radiologists into a single decision (recall the patient for additional workup or not). We found that, compared to single radiologists, any of these CI-rules both increases true positives (i.e., recalls of patients with cancer) and decreases false positives (i.e., recalls of patients without cancer), thereby overcoming one of the fundamental limitations to decision accuracy that individual radiologists face. Importantly, we find that all CI-rules systematically outperform even the best-performing individual radiologist in the respective group. Our findings demonstrate that CI can be employed to improve mammography screening; similarly, CI may have the potential to improve medical decision-making in a much wider range of contexts, including many areas of diagnostic imaging and, more generally, diagnostic decisions that are based on the subjective interpretation of evidence.

Effect of radiologists' diagnostic work-up volume on interpretive performance

PURPOSE

To examine radiologists' screening performance in relation to the number of diagnostic work-ups performed after abnormal findings are discovered at screening mammography by the same radiologist or by different radiologists.

MATERIALS AND METHODS

In an institutional review board-approved HIPAA-compliant study, the authors linked 651 671 screening mammograms interpreted from 2002 to 2006 by 96 radiologists in the Breast Cancer Surveillance Consortium to cancer registries (standard of reference) to evaluate the performance of screening mammography (sensitivity, false-positive rate [ FPR false-positive rate ], and cancer detection rate [ CDR cancer detection rate ]). Logistic regression was used to assess the association between the volume of recalled screening mammograms ("own" mammograms, where the radiologist who interpreted the diagnostic image was the same radiologist who had interpreted the screening image, and "any" mammograms, where the radiologist who interpreted the diagnostic image may or may not have been the radiologist who interpreted the screening image) and screening performance and whether the association between total annual volume and performance differed according to the volume of diagnostic work-up.

RESULTS

Annually, 38% of radiologists performed the diagnostic work-up for 25 or fewer of their own recalled screening mammograms, 24% performed the work-up for 0-50, and 39% performed the work-up for more than 50. For the work-up of recalled screening mammograms from any radiologist, 24% of radiologists performed the work-up for 0-50 mammograms, 32% performed the work-up for 51-125, and 44% performed the work-up for more than 125. With increasing numbers of radiologist work-ups for their own recalled mammograms, the sensitivity (P = .039), FPR false-positive rate (P = .004), and CDR cancer detection rate (P < .001) of screening mammography increased, yielding a stepped increase in women recalled per cancer detected from 17.4 for 25 or fewer mammograms to 24.6 for more than 50 mammograms. Increases in work-ups for any radiologist yielded significant increases in FPR false-positive rate (P = .011) and CDR cancer detection rate (P = .001) and a nonsignificant increase in sensitivity (P = .15). Radiologists with a lower annual volume of any work-ups had consistently lower FPR false-positive rate , sensitivity, and CDR cancer detection rate at all annual interpretive volumes.

CONCLUSION

These findings support the hypothesis that radiologists may improve their screening performance by performing the diagnostic work-up for their own recalled screening mammograms and directly receiving feedback afforded by means of the outcomes associated with their initial decision to recall. Arranging for radiologists to work up a minimum number of their own recalled cases could improve screening performance but would need systems to facilitate this workflow.