Ten-Year Survival after Postmastectomy Chest-Wall Irradiation in Breast Cancer.
Kunkler IH, Russell NS, Anderson N, Sainsbury R, Dixon JM, Cameron D, Loncaster J, Hatton M, Westenberg H, Clarke J, McCarty H, Evans R, Geropantas K, Wolstenholme V, Alhasso A, Woodings P, Barraclough L, Bayman N, Welch R, Muturi F, McEleney T, Burns J, Riddle K, Macdonald E, Dunlop J, Sergenson N, van Tienhoven G, Taylor KJ, Bartlett JMS, Piper T, Velikova G, Aird E, Chua B, Hurkmans C, Venables K, Williams LJ, Thomas JS, Hanby AM, Maclennan M, Cleator S, Verghese ET, Li Y, Wang S, Canney P, SUPREMO Trial Investigators, Sunil
Paper source
Ten-Year Survival after Postmastectomy Chest-Wall Irradiation in Breast Cancer.
This rigor review was examined and confirmed by Adcurare Editorial · July 6, 2026
How this rating was calculated▸
- IntegrityIntegrity concern−0.5★
- ReportingData & code availability partially met−0.25★
- Data/code availability incomplete
- Internal contradictions in the reported numbers
This Adcurare Rigor Review uses AI Rigor Reviewers trained on a curated corpus of high-fidelity and retracted papers, with expert supervision and curation. It can still make mistakes; verify each finding against the source before relying on it.
The manuscript is a well-conducted phase 3 RCT with strong methodological foundations in most dimensions. Weaknesses include incomplete reporting of biological variables (weight/health status, race/ethnicity), missing exact p-values for some secondary endpoints, and a vague data availability statement. These are fixable reporting gaps.
All eight dimensions were evaluated based on full-text review. The three independent reviewers agreed on most dimensions but diverged on biological variables (pass vs warn) and statistical analysis (pass vs warn); we weighed specific evidence to resolve these. The key resources dimension was rated pass (not not applicable) because radiotherapy is an investigational product. The statistical verification covered only 2 tests; all were consistent, but this does not validate the entire analysis.
12 major claims checked against the paper's own evidence: all adequately supported.
Recomputed 2 tests: 2 consistent, 0 inconsistent, 2 via agent-written checks.
1 integrity concern flagged (0 high).
4 copyedit issues flagged: mostly consistency, clarity, punctuation.
Checked 38 references: 34 verified — 4 not checked.
2 data/code links checked; 1 live.
Registered (1 ID: ClinicalTrials.gov). Reporting guideline cited: CONSORT.
The manuscript is near submission-ready but requires minor revisions before submission. The most critical issues are adding a concrete data availability statement and correcting the mislabeled patient counts in the subgroup analysis (events vs number of patients). Other high-priority fixes include reporting exact p-values for secondary endpoints and naming the statistical software.
- 1.HIGHdata codeAdd a concrete data availability statement in the main text describing the mechanism for requesting patient-level data (e.g., named data access committee, platform like YODA, or a URL), rather than only referencing a statement at NEJM.org.Without a clear data access mechanism, the paper fails reproducibility standards and may be returned by the journal.
- 2.HIGHcopyeditCorrect the subgroup analysis text that says 'the number of events for pN0 patients: 191 with irradiation, 211 without irradiation' – these are patient counts, not events, and the wording should be revised for accuracy.This internal contradiction (events vs patients) is confusing and could mislead readers; it was flagged by both the copyedit and integrity checks.
- 3.HIGHstatisticsReport exact p-values for all secondary endpoints (chest wall recurrence, DFS, DMFS) alongside the hazard ratios and confidence intervals.Missing exact p-values is a reporting gap that reduces transparency and makes it harder for readers to assess statistical significance for these outcomes.
- 4.HIGHstatisticsIdentify the statistical software (e.g., SAS version 9.4, Stata 16, R 4.0) used for all analyses, including version number.Standard reporting guidelines (CONSORT, ICMJE) require naming software to ensure reproducibility; this is a simple addition.
- 5.MEDIUMreportingAdd participants' race/ethnicity and a measure of health status (e.g., ECOG performance status or BMI) to Table 1.These variables are standard for clinical trial demographics and support generalizability assessment; their absence was noted as a biological_variables gap.
- 6.MEDIUMreportingAdd a statement that this trial was reported in accordance with CONSORT 2010 guidelines, and confirm that a CONSORT checklist was submitted.Explicitly naming the reporting guideline improves transparency and compliance with journal requirements.
- 7.MEDIUMdata codeIf custom code was used for analysis (e.g., data management scripts, statistical routines), deposit it in a public repository (GitHub, Zenodo) with a DOI or link, and mention this in the paper.Code sharing is increasingly expected for reproducibility; even if no custom code was used, stating 'no custom code was used' would clarify.
- 8.LOWreportingAdd a brief justification for enrolling only women (e.g., 'as the study population was limited to women with breast cancer, male patients were not eligible'), or note that male breast cancer was rare and not included per standard trial design.Although the disease is female-predominant, explicitly stating the rationale for single-sex enrollment closes a minor reporting gap.
- 9.LOWreportingAdd a statement acknowledging the open-label design and its potential impact on assessment of subjective outcomes (e.g., toxicity recording).Transparency about blinding limitations adds credibility and is a good practice for non-blinded intervention trials.
- 10.LOWreportingConsider depositing the full trial protocol and statistical analysis plan in a public repository (e.g., ClinicalTrials.gov or Zenodo) and cite the DOI in the paper.Making protocol and SAP publicly available strengthens reproducibility and allows readers to confirm pre-specification of analyses.
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