Evidence map›Paper›PMID 39228986›Full record

ArticleFrontiers in oncology2024

Pathological PCI as a prognostic marker of survival after neoadjuvant chemotherapy in patients undergoing interval cytoreduction with or without HIPEC in FIGO stage IIIC high grade serous ovarian cancer.

Snita Sinukumar, Dileep Damodaran, Deepika S, Sanjay Piplani

Abstract read
In one paragraph

Article in Frontiers in oncology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed, 1 pooled it
–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

3 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  3. 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

4 authors.

Snita SinukumarDepartment of Surgical Oncology, Jehangir Hospital, Pune, India.
Dileep DamodaranDepartment of Surgical Oncology, MVR Cancer Centre and Research Institute, Calicut, India.
Deepika SDepartment of Surgical Oncology, MVR Cancer Centre and Research Institute, Calicut, India.
Sanjay PiplaniDepartment of Surgical Oncology, Jehangir Hospital, Pune, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: To determine the best possible value of pathological PCI (pPCI) as a prognostic marker for survival in high-grade serous epithelial ovarian cancer patients in patients treated with neoadjuvant chemotherapy and interval cytoreductive surgery. Methods: All patients with FIGO stage IIIC high-grade serous ovarian carcinoma were included. Receiver operating curves (ROC) were used to determine the best possible score for pPCI in predicting survival. Survival curves were calculated using the Kaplan-Meier test, and factors affecting survival were compared using the log-rank test. Results: From January 2018 to January 2024, 171 patients who underwent interval cytoreductive surgery were included. Complete cytoreduction was achieved in 88% of the patients. ROC curves determined a (pPCI) cut-off value of 8 as the best possible score for predicting survival with a sensitivity of 82% and specificity of 67% (Youden's Index = 0.60). pPCI with a cut-off value of 8 showed improved OS (p = 0.002) and DFS, (p = 0.001) in both univariate and multivariate analyses. Conclusion: Following interval cytoreductive surgery, despite optimal complete cytoreductive surgery, a pathological PCI of 8 is a poor prognostic indicator of survival and may serve as a surrogate clinical marker for guiding clinicians in adjuvant treatment, especially in resource-driven settings in the real world.

Indexed as

high-grade serous ovarian cancerHIPECinterval cytoreductive surgeryKELIMpathological PCI

Identifiers

PMID39228986
PMCPMC11368729

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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.