ReviewCancers2020
Identifying Ovarian Cancer in Symptomatic Women: A Systematic Review of Clinical Tools.
Review in Cancers, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 2 of them syntheses that pooled 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.
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.
Who cites it
13 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Risk prediction models for symptomatic patients with bladder and kidney cancer: a systematic review.The British journal of general practice : the journal of the Royal College of General Practitioners · 2022Pooled it
- Research Progress and Applications of Multivalent, Multispecific and Modified Nanobodies for Disease Treatment.Frontiers in immunology · 2021Pooled it
- Using large language models to identify prediagnostic clinical features of ovarian cancer from healthcare records: a population-based case-control study.The British journal of general practice : the journal of the Royal College of General Practitioners · 2026Article
- Diagnostic Timing and Ovarian Cancer Survival.JAMA network open · 2026Article
- Circ-RNF111 Promotes Proliferation of Ovarian Cancer Cell SKOV-3 by Targeting the MiR-556-5p/CCND1 Axis.Biochemical genetics · 2024Article
- Cancer incidence and competing mortality risk following 15 presenting symptoms in primary care: a population-based cohort study using electronic healthcare records.BMJ oncology · 2024Article
- Pain nursing for gynecologic cancer patients.Frontiers in oncology · 2023Review
- Early diagnosis of symptomatic ovarian cancer in primary care in the UK: opportunities and challenges.Primary health care research & development · 2022Article
- Special Issue "Gynaecological Cancers Risk: Breast Cancer, Ovarian Cancer and Endometrial Cancer".Cancers · 2022Article
- A nomogram model based on clinical markers for predicting malignancy of ovarian tumors.Frontiers in endocrinology · 2022Article
- Modified HE4, CA125, and ROMA cut-off values and predicted probability of ovarian tumor in Chinese patients.Gland surgery · 2021Article
- Article
- Overexpression of NPTX2 Promotes Malignant Phenotype of Epithelial Ovarian CarcinomaFrontiers in oncology · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
Abstract
In the absence of effective ovarian cancer screening programs, most women are diagnosed following the onset of symptoms. Symptom-based tools, including symptom checklists and risk prediction models, have been developed to aid detection. The aim of this systematic review was to identify and compare the diagnostic performance of these tools. We searched MEDLINE, EMBASE and Cochrane CENTRAL, without language restriction, for relevant studies published between 1 January 2000 and 3 March 2020. We identified 1625 unique records and included 16 studies, evaluating 21 distinct tools in a range of settings. Fourteen tools included only symptoms; seven also included risk factors or blood tests. Four tools were externally validated-the Goff Symptom Index (sensitivity: 56.9-83.3%; specificity: 48.3-98.9%), a modified Goff Symptom Index (sensitivity: 71.6%; specificity: 88.5%), the Society of Gynaecologic Oncologists consensus criteria (sensitivity: 65.3-71.5%; specificity: 82.9-93.9%) and the QCancer Ovarian model (10% risk threshold-sensitivity: 64.1%; specificity: 90.1%). Study heterogeneity precluded meta-analysis. Given the moderate accuracy of several tools on external validation, they could be of use in helping to select women for ovarian cancer investigations. However, further research is needed to assess the impact of these tools on the timely detection of ovarian cancer and on patient survival.
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Registered trials
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.