ArticleBMC women's health2022
Pathways to ovarian cancer diagnosis: a qualitative study.
Article in BMC women's health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.
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Who cites it
20 citing papers in PubMed, 31 citations in OpenAlex.
- [Medical prior-guided TabMap deep learning model for ovarian cancer prediction and interpretability analysis].Nan fang yi ke da xue xue bao = Journal of Southern Medical University · 2026Article
- Ovarian cancer presentation and management in sub-Saharan Africa: a scooping review protocal.Malawi medical journal : the journal of Medical Association of Malawi · 2026Review
- Limited Clinical Benefit of Immune Checkpoint Inhibition in Ovarian Cancer with Opportunities in Selected Subtypes.International journal of molecular sciences · 2026Review
- Factors influencing delays in the diagnosis and treatment of bipolar disorder in adolescents and young adults: systematic scoping review.BJPsych open · 2026Review
- Exploring the anti-cancer potential of gut microbiota-derived short-chain fatty acids in ovarian cancer: a comparative analysis of sodium butyrate and sodium propionate on proliferation, cell cycle, and apoptosis.Cancer cell international · 2026Article
- MRI of combination immunotherapy in an epithelial ovarian cancer preclinical model.Npj imaging · 2026Article
- Diagnostic Timing and Ovarian Cancer Survival.JAMA network open · 2026Article
- A fast-progressing orthotopic ovarian cancer model reveals synergistic antitumor effects of AXL-targeting nanobodies and Olaparib.Gynecologic oncology reports · 2025Article
- Longitudinal point-of-care ultrasound training program for emergency medicine faculty in Oman: a Kirkpatrick model approach.BMC medical education · 2025Article
- Clinical Evaluation of a Multi-Omic Diagnostic Model for Early-Stage Ovarian Cancer Detection.Diagnostics (Basel, Switzerland) · 2025Article
- Proteomic alterations in ovarian cancer-Predicting residual disease status using artificial intelligence and SHAP-based biomarker interpretation.Frontiers in medicine · 2025Article
- Article
- Improving Specificity for Ovarian Cancer Screening Using a Novel Extracellular Vesicle-Based Blood Test: Performance in a Training and Verification Cohort.The Journal of molecular diagnostics : JMD · 2024Article
- Evaluation of online text-based information resources of gynaecological cancer symptoms.Cancer medicine · 2024Article
- Women with ovarian cancer's information seeking and avoidance behaviors: an interview study.JAMIA open · 2024Article
- Construction of an exosome-associated miRNA-mRNA regulatory network and validation ofTranslational cancer research · 2024Article
- CRABP2 affects chemotherapy resistance of ovarian cancer by regulating the expression of HIF1α.Cell death & disease · 2024Article
- Article
- Pathways to lung cancer diagnosis among individuals who did not receive lung cancer screening: a qualitative study.BMC primary care · 2023Article
- Review
Corrections and comments
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Authors and funding
10 authors at 5 institutions in 1 country.
Funding
Abstract
backgroundOvarian cancer is often diagnosed at a late stage, when survival is poor. Qualitative narratives of patients' pathways to ovarian cancer diagnoses may identify opportunities for earlier cancer detection and, consequently, earlier stage at diagnosis.
methodsWe conducted semi-structured interviews of ovarian cancer patients and survivors (n = 14) and healthcare providers (n = 11) between 10/2019 and 10/2021. Interviews focused on the time leading up to an ovarian cancer diagnosis. Thematic analysis was conducted by two independent reviewers using a two-phase deductive and inductive coding approach. Deductive coding used a priori time intervals from the validated Model of Pathways to Treatment (MPT), including self-appraisal and management of symptoms, medical help-seeking, diagnosis, and pre-treatment. Inductive coding identified common themes within each stage of the MPT across patient and provider interviews.
resultsThe median age at ovarian cancer diagnosis was 61.5 years (range, 29-78 years), and the majority of participants (11/14) were diagnosed with advanced-stage disease. The median time from first symptom to initiation of treatment was 2.8 months (range, 19 days to 4.7 years). The appraisal and help-seeking intervals contributed the greatest delays in time-to-diagnosis for ovarian cancer. Nonspecific symptoms, perceptions of health and aging, avoidant coping strategies, symptom embarrassment, and concerns about potential judgment from providers prolonged the appraisal and help-seeking intervals. Patients and providers also emphasized access to care, including financial access, as critical to a timely diagnosis.
conclusionInterventions are urgently needed to reduce ovarian cancer morbidity and mortality. Population-level screening remains unlikely to improve ovarian cancer survival, but findings from our study suggest that developing interventions to improve self-appraisal of symptoms and reduce barriers to help-seeking could reduce time-to-diagnosis for ovarian cancer. Affordability of care and insurance may be particularly important for ovarian cancer patients diagnosed in the United States.
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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 Socratic graph.