The following peer review from Dr. Shannan Lynch was published on 4/23/2026

Mughal et al. builds on prior work (Mughal et al. 2025) that analyzed pre- and post-FDAAA reporting compliance. This analysis performed a similar evaluation, honing reporting compliance at the sponsor level for trials completed between 2017-2023 (post-FDAAA).

Abstract Section:

Under the Conclusion header, consider replacing:

-the first sentence with “This analysis — the first to comprehensively examine compliance with FDAAA 801 at the individual sponsor level — reveals significant disparities in reporting practices". Reason being, the sentence is front-loaded in such as way the subject of the sentence gets lost at the end of the sentence.

-the last sentence with "Achieving a higher standard of results reporting should remain....". Reason being, the word chain reads unnaturally.

Background Section 1:

Consider clarifying for novice readers that the completion definition is the “primary” completion date. For example, perhaps rewrite the following sentence “Under this rule, starting April 18, 2017, responsible parties are required to report trial no later than 12 months after the trial's primary completion date or within 12 months after the date of early termination, unless legally justifiable."

Methods Section 1:

-Define HLACT

-Section 2.2:

-Consider replacing “Inclusion Criteria” with “Analysis Inclusion Criteria” to highlight the different between the criteria used in the analysis vs. other definitions (HLACT, inclusion in FDAAA, etc.)

-You direct the reader to Clinicaltrials.gov to obtain the definition of the primary completion date. I recommend including this definition at least as a supplement for the reader’s convenience, but also for temporality (i.e., what if the definition changes in 5 years).

-Section 2.3:

-Readability edit: Insert a hard Enter between the last two paragraph to better separate the two topics (after “to be considered academic.” and before “This categorization…”

-RE: Last paragraph. The utility of including data outside of the statistical computing is unclear. If a Sponsor does not fit into a single clearly defined group then the value including the data seems outside of the research question.

-Section 2.4

-RE: “Rankings include all sponsors, not just the sponsors that are categorized in Section 2.3.” This sentence is unclear. Do you mean the rankings as far as the entities listed in the tables, or the rankings associated with the Wilson LCB method? If it is the latter, then why include data in the computation that does not meet the analysis criteria? If it is the former, can you clarify the utility of listing these Sponsors in the paper?

-Perhaps define UEI for readers who may not know this is NIH's unique entity identifier.

Results Section 3:

-Table 2:

-Consider reporting the number of compliant trials explicitly — this would give readers immediate access to the full picture without needing to derive the numerator from the percentage.

-For better readability, justify all columns left.

-Can you clarify if the “All Results Rate” column reflects the percentage that report at any time after completion (i.e., within 12 months and >12 months)? I think you state this under Table 4, but it is worth clarifying for the reader, as this is a source of strength for the trial.

-Section 3.2:

-Can you clarify why there are sponsors in the table (e.g., Mayo, NYU, Mass Gen) that do not conform to categories listed in criteria? If these are to be included, I suggest including how bias was controlled in including said sponsors, and again, clarify the utility of this data.

Discussion Section 4:

-Perhaps it is worth mentioning that on-trend with the Mughal et al 2025 analysis, compliance is improving overall.

-Consider adding a “Strengths” section. For example, using Wilson LCB is a conservative approach for balancing the variability in trials across entities. In addition, if the column “All Results Rate” does include reporting at any time, the side-by-side of compliant trials vs all-results reporting provides a policy-relevant tool—why is it difficult to report within 12 months, but eventually, many do post the study data on the website? This study provides useful data to this question and could spawn additional research. I think the cross-database mapping was rather clever and improved the robustness of the analysis.