Evidence map›Paper›PMID 41228215›Full record

ArticleCancers2025

P-POSSUM Falls Short: Predicting Morbidity in Ovarian Cancer (OC) Cytoreductive Surgery.

Michail Sideris, Mark R Brincat, Oleg Blyuss, Samuel George Oxley, Jacqueline Sia, Ashwin Kalra, Xia Wei, Caitlin T Fierheller, Subhasheenee Ganesan, Rowan E Miller and 12 more

Abstract read
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In one paragraph

Article in Cancers, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

22 authors.

Michail SiderisWolfson Institute of Population Health, Queen Mary University of London, London EC1M 6BQ, UK.ORCID 0000-0002-4199-6700
Mark R BrincatDepartment of Gynaecological Oncology, Barts Health NHS Trust, Royal London Hospital, London E1 1BB, UK.
Oleg BlyussWolfson Institute of Population Health, Queen Mary University of London, London EC1M 6BQ, UK.ORCID 0000-0002-0194-6389
Samuel George OxleyWolfson Institute of Population Health, Queen Mary University of London, London EC1M 6BQ, UK.ORCID 0000-0003-1967-813X
Jacqueline SiaWolfson Institute of Population Health, Queen Mary University of London, London EC1M 6BQ, UK.
Ashwin KalraWolfson Institute of Population Health, Queen Mary University of London, London EC1M 6BQ, UK.ORCID 0000-0002-5541-226X
Xia WeiWolfson Institute of Population Health, Queen Mary University of London, London EC1M 6BQ, UK.
Caitlin T FierhellerWolfson Institute of Population Health, Queen Mary University of London, London EC1M 6BQ, UK.
Subhasheenee GanesanWolfson Institute of Population Health, Queen Mary University of London, London EC1M 6BQ, UK.
Rowan E MillerDepartment of Gynaecological Oncology, Barts Health NHS Trust, Royal London Hospital, London E1 1BB, UK.
Fatima El-KhoulyDepartment of Medical Oncology, Barking, Havering and Redbridge University Hospitals NHS Trust, Romford RM1 2BA, UK.
Mevan GooneratneDepartment of Gynaecological Oncology, Barts Health NHS Trust, Royal London Hospital, London E1 1BB, UK.
Tom AbbottDepartment of Gynaecological Oncology, Barts Health NHS Trust, Royal London Hospital, London E1 1BB, UK.
Ching Ling PangDepartment of Gynaecological Oncology, Barts Health NHS Trust, Royal London Hospital, London E1 1BB, UK.
Parvesh VermaDepartment of Gynaecological Oncology, Barts Health NHS Trust, Royal London Hospital, London E1 1BB, UK.
Seema ShahDepartment of Gynaecological Oncology, Barts Health NHS Trust, Royal London Hospital, London E1 1BB, UK.
Alexandra LawrenceDepartment of Gynaecological Oncology, Barts Health NHS Trust, Royal London Hospital, London E1 1BB, UK.
Arjun JeyarajahDepartment of Gynaecological Oncology, Barts Health NHS Trust, Royal London Hospital, London E1 1BB, UK.
Elly BrockbankDepartment of Gynaecological Oncology, Barts Health NHS Trust, Royal London Hospital, London E1 1BB, UK.
Saurabh PhadnisDepartment of Gynaecological Oncology, Barts Health NHS Trust, Royal London Hospital, London E1 1BB, UK.
James DilleyDepartment of Gynaecological Oncology, Barts Health NHS Trust, Royal London Hospital, London E1 1BB, UK.
Ranjit ManchandaWolfson Institute of Population Health, Queen Mary University of London, London EC1M 6BQ, UK.ORCID 0000-0003-3381-5057

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveThe P-POSSUM scale is widely used in predicting perioperative morbidity and mortality. Evidence on the performance of P-POSSUM in predicting outcomes after cytoreductive surgery (CRS) for ovarian cancer (OC) is limited. In this study, we assess how well P-POSSUM predicts morbidity in OC CRS and explore whether incorporating additional clinical variables can enhance its predictive accuracy. We retrospectively collected data on consecutive patients undergoing OC CRS within a tertiary gynaecologic oncology network. The collected information included demographic characteristics, P-POSSUM morbidity and mortality scores, Edmonton Frail Scale (EFS) scores, preoperative serum albumin levels, and observed 30-day postoperative morbidity and mortality, classified using the Clavien-Dindo (CD) scale. The predictive performance of P-POSSUM was evaluated using receiver operating characteristic (ROC) curves to calculate sensitivity and specificity. A stepwise regression analysis was then applied to identify additional variables that could improve model performance, incorporating preoperative covariates. The final model incorporated parameters chosen through bootstrap investigation of the model variability (stepAIC). Predicted versus observed morbidity was calibrated and performance compared between P-POSSUM and the final model.

resultsOf 161 sequential OC patients, 95 (59%) underwent primary, 45 (28%) interval, and 21 (13%) delayed CRS. The mean age was 66.4 (95%CI: 60-75) and duration of surgery was 223 mins (95%CI: 142-279). Sixty-five (40.3%) patients had ≥1 postoperative complication. Two deaths were reported. Among the observed complications, 4 patients (6.1%) experienced CD4, 10 patients (15.3%) CD3, 38 patients (58.5%) CD2, and 11 patients (16.9%) CD1 events. The mean P-POSSUM-predicted morbidity and mortality were 59.5% (95%CI: 56.7-62.3%) and 5.86% (95%CI: 5.02-6.70%), respectively. The area under the curve (AUC) for P-POSSUM in predicting morbidity and mortality was 0.539 (

conclusionsThe P-POSSUM scale shows poor performance for predicting morbidity in OC CRS. New validated and accurate model(s) are necessary for predicting surgical morbidity. Our proposed model incorporates additional variables to improve P-POSSUM's performance. This requires further development and validation.

Indexed as

cytoreductive surgerymorbidity prediction modelovarian cancerP-POSSUMsurgical morbidity

Identifiers

PMID41228215
PMCPMC12606732

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.