OA: Obesity and survival among women with ovarian cancer: results from the Ovarian Cancer Association Consortium Ovarian Cancer and Us OVARIAN CANCER and US Ovarian Cancer and Us

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Saturday, December 31, 2016

OA: Obesity and survival among women with ovarian cancer: results from the Ovarian Cancer Association Consortium

the Ovarian Cancer Association Consortium

 As ovarian cancer remains a highly fatal disease and the prevalence of obesity continues to increase, studies focusing on causal mechanisms involved in adverse survival are needed.
 A recent meta-analysis of 14 studies concluded that women with ovarian cancer, who were obese, had 17% worse survival compared with those of normal weight (Protani et al, 2012). However, the studies in this meta-analysis varied greatly in the timing of obesity measurement: from usual adult weight to weight at the time of diagnosis, or at the commencement of chemotherapy. Most of the studies included had a relatively small sample size (median=301) and, as a consequence, variation by histologic subtype could not be investigated. Furthermore, few studies had examined progression-free survival (PFS) or ovarian cancer-specific survival.
 Among the 21 OCAC studies, 756 (5.3%) women were with missing BMI information. Of the 12390 women included in the analyses, BMI ranged from 13.7 to 68.3kgm−2. Three hundred and seven women were underweight (BMI <18.5) and 71 (0.6%) had BMI values >50kgm−2.
Observational studies have reported a modest association between obesity and risk of ovarian cancer; however, whether it is also associated with survival and whether this association varies for the different histologic subtypes are not clear. We undertook an international collaborative analysis to assess the association between body mass index (BMI), assessed shortly before diagnosis, progression-free survival (PFS), ovarian cancer-specific survival and overall survival (OS) among women with invasive ovarian cancer.


We used original data from 21 studies, which included 12390 women with ovarian carcinoma. We combined study-specific adjusted hazard ratios (HRs) using random-effects models to estimate pooled HRs (pHR). We further explored associations by histologic subtype.......


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