Mark H Ebell1, MaryBeth B Culp2, Taylor J Radke2. 1. Department of Epidemiology and Biostatistics, College of Public Health, University of Georgia, Athens, Georgia. Electronic address: ebell@uga.edu. 2. Department of Epidemiology and Biostatistics, College of Public Health, University of Georgia, Athens, Georgia.
Abstract
CONTEXT: Ovarian cancer is common and has significant morbidity and mortality, partly because it is often diagnosed at a late stage. This study sought to determine the accuracy of individual symptoms and combinations of symptoms for the diagnosis of ovarian cancer. EVIDENCE ACQUISITION: MEDLINE was searched, identifying 2,492 abstracts, reviewing 71 articles in full, and ultimately identifying 17 studies published between 2001 and 2014 that met the inclusion criteria. Data were abstracted by two researchers, and quality was assessed using the QUADAS-2 criteria adapted to the study question. Bivariate random effects meta-analysis was used where possible, and heterogeneity and threshold effects were explored using receiver operating characteristic curves. Data were analyzed in 2015. EVIDENCE SYNTHESIS: Most studies were at high risk of bias, primarily because of case-control design or differential verification bias. The highest positive likelihood ratios (LRs+) were found for presence of abdominal mass (LR+, 30.0); abdominal distension or increased girth (LR+, 16.0); abdominal or pelvic pain (LR+, 10.4); abdominal or pelvic bloating (LR+, 9.3); loss of appetite (LR+, 9.2); and a family history of ovarian cancer (LR+, 7.5). No symptoms were helpful at ruling out ovarian cancer when absent. The Ovarian Cancer Symptom Index was validated in five studies and (after excluding one outlier with different inclusion criteria) was 63% sensitive and 95% specific (LR+, 12.6; LR-, 0.39). Two other symptom scores had not been validated prospectively. CONCLUSIONS: Several individual signs and symptoms significantly increase the likelihood of ovarian cancer when present. More work is needed to validate decision rules and develop new decision support tools integrating risk factors, symptoms, and possibly biomarkers to identify women at increased ovarian cancer risk.
CONTEXT: Ovarian cancer is common and has significant morbidity and mortality, partly because it is often diagnosed at a late stage. This study sought to determine the accuracy of individual symptoms and combinations of symptoms for the diagnosis of ovarian cancer. EVIDENCE ACQUISITION: MEDLINE was searched, identifying 2,492 abstracts, reviewing 71 articles in full, and ultimately identifying 17 studies published between 2001 and 2014 that met the inclusion criteria. Data were abstracted by two researchers, and quality was assessed using the QUADAS-2 criteria adapted to the study question. Bivariate random effects meta-analysis was used where possible, and heterogeneity and threshold effects were explored using receiver operating characteristic curves. Data were analyzed in 2015. EVIDENCE SYNTHESIS: Most studies were at high risk of bias, primarily because of case-control design or differential verification bias. The highest positive likelihood ratios (LRs+) were found for presence of abdominal mass (LR+, 30.0); abdominal distension or increased girth (LR+, 16.0); abdominal or pelvic pain (LR+, 10.4); abdominal or pelvic bloating (LR+, 9.3); loss of appetite (LR+, 9.2); and a family history of ovarian cancer (LR+, 7.5). No symptoms were helpful at ruling out ovarian cancer when absent. The Ovarian Cancer Symptom Index was validated in five studies and (after excluding one outlier with different inclusion criteria) was 63% sensitive and 95% specific (LR+, 12.6; LR-, 0.39). Two other symptom scores had not been validated prospectively. CONCLUSIONS: Several individual signs and symptoms significantly increase the likelihood of ovarian cancer when present. More work is needed to validate decision rules and develop new decision support tools integrating risk factors, symptoms, and possibly biomarkers to identify women at increased ovarian cancer risk.
Authors: Mary C Puckett; Julie S Townsend; Cynthia A Gelb; Polly Hager; Amy Conlon; Sherri L Stewart Journal: J Cancer Educ Date: 2018-12 Impact factor: 2.037