OBJECTIVE: To test the hypothesis that clinical variables, including the patient's symptoms, symptom severity, and co-morbidity, affect the survival rate in patients with ovarian cancer. METHODS: We reviewed the records of 137 cases of ovarian cancer diagnosed and treated between January 1987 and June 1992, and extracted data regarding patients' demographic characteristics, symptoms, medical co-morbidity, stage of disease, tumor histology and grade, treatment, and clinical course. RESULTS: Once cases of borderline tumors were excluded, the overall 3-year and 4-year mortality rate were 38% and 49%, respectively. There was an decrease in 4-year survival with more advanced symptom type ranging from 85% in asymptomatic women to 38% in women with complex symptoms (log rank, p = 0.005). Medical co-morbidity was not found to affect survival in the cohort studied. We performed multivariable analysis using a Cox proportional hazards model and confirmed that the symptom stage was highly prognostic even after controlling for FIGO stage, age and co-morbidity (p = 0.004). CONCLUSION: We found that clinical variables such as patient's symptoms, were associated with prognosis. Symptom classification is a necessary and important component in a system of prognostic stratification for ovarian cancer.
OBJECTIVE: To test the hypothesis that clinical variables, including the patient's symptoms, symptom severity, and co-morbidity, affect the survival rate in patients with ovarian cancer. METHODS: We reviewed the records of 137 cases of ovarian cancer diagnosed and treated between January 1987 and June 1992, and extracted data regarding patients' demographic characteristics, symptoms, medical co-morbidity, stage of disease, tumor histology and grade, treatment, and clinical course. RESULTS: Once cases of borderline tumors were excluded, the overall 3-year and 4-year mortality rate were 38% and 49%, respectively. There was an decrease in 4-year survival with more advanced symptom type ranging from 85% in asymptomatic women to 38% in women with complex symptoms (log rank, p = 0.005). Medical co-morbidity was not found to affect survival in the cohort studied. We performed multivariable analysis using a Cox proportional hazards model and confirmed that the symptom stage was highly prognostic even after controlling for FIGO stage, age and co-morbidity (p = 0.004). CONCLUSION: We found that clinical variables such as patient's symptoms, were associated with prognosis. Symptom classification is a necessary and important component in a system of prognostic stratification for ovarian cancer.
Authors: John K Chan; Chunqiao Tian; Joshua P Kesterson; Bradley J Monk; Daniel S Kapp; Brittany Davidson; Sharon Robertson; Larry J Copeland; Joan L Walker; Robert M Wenham; Yovanni Casablanca; Nick M Spirtos; Krishnansu S Tewari; Jeffrey G Bell Journal: Obstet Gynecol Date: 2022-02-01 Impact factor: 7.623
Authors: Eileen H Shinn; Daniel J Lenihan; Diana L Urbauer; Karen M Basen-Engquist; Alan Valentine; Laura Palmero; Myrshia L Woods; Pooja Patel; Alpa M Nick; Mian M K Shahzad; Rebecca L Stone; Antoinette Golden; Emma Atkinson; Susan K Lutgendorf; Anil K Sood Journal: Cancer Epidemiol Biomarkers Prev Date: 2013-09-17 Impact factor: 4.254
Authors: Charlotte E Joslin; Katherine C Brewer; Faith G Davis; Kent Hoskins; Caryn E Peterson; Heather A Pauls Journal: Gynecol Oncol Date: 2014-08-28 Impact factor: 5.482