Evidence map›Paper›PMID 41846667›Full record

ArticleCureus2026

Rethinking Epithelial Ovarian Cancer Surveillance Protocols.

Divya P Vuppu, Priya Bhati, Pranidhashree C A, Sheejamol V S

Abstract read
In one paragraph

Article in Cureus, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Divya P VuppuGynaecological Oncology, Amrita Institute of Medical Sciences and Research, Kochi, IND.
Priya BhatiGynaecological Oncology, Amrita Institute of Medical Sciences and Research, Kochi, IND.
Pranidhashree C AGynaecological Oncology, Amrita Institute of Medical Sciences and Research, Kochi, IND.
Sheejamol V SBiostatistics, Amrita Institute of Medical Sciences and Research, Kochi, IND.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThis study aims to identify the main method of recurrence detection, site of recurrence, and three- and five-year disease-free survival (DFS) rates of ovarian cancer while considering the financial burden on the patient and family.

methodsTwo hundred and ten consecutive epithelial ovarian cancer cases from the hospital-based cancer registry between January 2015 and June 2023, in which patients had documented remission after completing primary treatment and were diagnosed with first recurrence, were included in the study. These four modes of detection of recurrence were considered: symptoms (abdominal pain, bloating, abdominal distention, etc.), physical findings, raised tumor marker (CA-125), and imaging.

resultsThis study found that raised CA-125 is the primary detection method in 59% of cases, followed by symptoms (21.4%). Imaging identifies recurrence first in 15.2% of cases and physical examination in 4.3%. Observed patterns suggest an association between the site of recurrence - particularly the pelvis and abdominopelvic peritoneum - and the method by which recurrence was first detected. Physical exams are most effective for pelvic recurrences (72.8%), while symptoms and CA-125 levels are higher for abdominopelvic peritoneal recurrences (72.7% and 68.8%, respectively). Patients have a median of six hospital visits, travel a median distance of 70 km for each visit, incur direct costs of ₹9000, and have a median DFS of 18 months.

conclusionThe study highlights elevated CA-125 and symptoms as primary recurrence indicators, questioning physical exam efficacy, and stresses the financial and emotional burden of frequent hospital visits.

Indexed as

financial burdenovarian cancerrecurrencesurveillancetumour marker

Identifiers

PMID41846667
PMCPMC12989704

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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.