Outcomes of Different Quality of Life Assessment Modalities After Breast Cancer Therapy
Bibliographic record
Abstract
Importance: Improvement in clinical understanding of the priorities of patients with breast cancer (BC) regarding postoperative aesthetic outcomes (AOs) is needed. Objective: To assess expert panel and computerized evaluation modalities against patient-reported outcome measures (PROMs), the gold standard of AO assessment, in patients after surgical management of BC. Data Sources: Embase, MEDLINE, PsycINFO, PubMed, the Cochrane Central Register of Controlled Trials, the World Health Organization International Clinical Trials Registry Platform, and ClinicalTrials.gov were interrogated from inception through August 5, 2022. Search terms included breast conserving AND aesthetic outcome AND breast cancer. Ten observational studies were eligible for inclusion, with the earliest date of database collection on December 15, 2022. Study Selection: Studies with at least 1 pairwise comparison (PROM vs expert panel or PROM vs computerized evaluation with Breast Cancer Conservation Treatment cosmetic results [BCCT.core] software) were considered eligible if they included patients who received BC treatment with curative intent. Studies reporting solely on risk reduction or benign surgical procedures were excluded to ensure transitivity. Data Extraction and Synthesis: Two independent reviewers extracted study data with an independent cross-check from a third reviewer. The quality of included observational studies was assessed using the Newcastle-Ottawa Scale, and the level of evidence quality was assessed using the Grading of Recommendations Assessment, Development and Evaluation tool. Confidence in network meta-analysis results was analyzed with the Confidence in Network Meta-analysis semiautomated tool. Effect size was reported using random-effects odds ratios (ORs) and cumulative ratios of ORs with 95% credibility intervals (CrIs). Main Outcomes and Measures: The primary outcome of this network meta-analysis was modality (expert panel or computer software) discordance from PROMs. Four-point Likert responses across PROMs, expert panel assessment, and BCCT.core evaluation of AOs were assessed. Results: A total of 10 observational studies including 3083 patients (median [IQR] age, 59 [50-60] years; median [range] follow-up, 39.0 [22.5-80.5] months) with reported AOs were assessed and homogenized in 4 distinct Likert response groups (excellent, very good, satisfactory, and bad). Overall network incoherence was low (χ22 = 0.35; P = .83). Overall, panel and software modalities graded AO outcomes worse than PROMs. Specifically, for excellent vs all other responses, the panel to PROM ratio of ORs was 0.30 (95% CrI, 0.17-0.53; I2 = 86%) and the BCCT.core to PROM ratio of ORs was 0.28 (95% CrI, 0.13-0.59; I2 = 95%), while the BCCT.core to panel ratio of ORs was 0.93 (95% CrI, 0.46-1.88; I2 = 88%). Conclusions and Relevance: In this study, patients scored AOs higher than both expert panels and computer software. Standardization and supplementation of expert panel and software AO tools with racially, ethnically, and culturally inclusive PROMs is needed to improve clinical evaluation of the journey of patients with BC and to prioritize components of therapeutic outcomes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".