The Importance of Patient-Reported Outcome Measures (PROMs) in Oncological Vulvoperineal Defect Reconstruction: A Systematic Review
Bibliographic record
Abstract
BACKGROUND: Patient-reported outcome measures (PROMs) have gained increased importance in assessing outcomes after reconstructive surgery. This also applies to the reconstruction of vulvoperineal defects after resection of gynecological or colorectal cancers in women. The objective of this study is to analyze the current state of PROM tool use within this patient population. METHODS: By systematic literature searches in Embase, Medline, and Web of Science, English-language studies published after 1980, including randomized controlled trials, cohort studies, and case series reporting on vulvoperineal defect reconstruction, which were included if they also analyzed quality of life (QoL) and/or PROMs. The PROM tools used by each study were extracted, analyzed, and compared. RESULTS: The primary search yielded 2576 abstracts, of which 395 articles were retrieved in full text. Of these, 50 reported on vulvoperineal defect reconstruction, among which 27 studies analyzing QoL were found. Of those, 17 met the inclusion criteria for this systematic review. After full-text screening, 14 different PROM tools and 5 individual, non-standardized questionnaires were identified. Only 22% of studies used a validated PROM tool. CONCLUSION: Far too few studies currently use PROM tools to assess outcomes in oncological vulvoperineal defect reconstruction. Less than half of the used PROMs are validated. No PROM was designed to specifically measure QoL in this patient population. The standardized implementation of a validated PROM tool in the clinical treatment of this patient population is an essential step to improve outcomes, enable the comparison of research, and support evidence-based treatment approaches.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".