2015
DOI: 10.1038/srep11720
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Comorbidity and survival among women with ovarian cancer: evidence from prospective studies

Abstract: The relationship between comorbidity and ovarian cancer survival has been controversial so far. Therefore, we conducted a meta-analysis to summarize the existing evidence from prospective studies on this issue. Relevant studies were identified by searching the PubMed, EMBASE, and ISI Web of Science databases through the end of January 2015. Two authors independently performed the eligibility evaluation and data abstraction. Random-effects models were used to estimate summary hazard ratios (HRs) and 95% confide… Show more

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Cited by 23 publications
(18 citation statements)
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“…If the selected study did not include a risk estimate, we calculated the unadjusted RR and the 95% CI from the raw data for simplicity [16,17,23,24,[48][49][50][51]. Estimates were pooled using a random-effects model to calculate the summarized RRs and 95% CI [52][53][54]. If the selected studies reported the results of cardiovascular malformations as other outcomes but with similar definitions [e.g., congenital heart defect (CHD) or cardiac malformations], we combined the risk estimate to calculate the summarized RR of cardiovascular malformation.…”
Section: Discussionmentioning
confidence: 99%
“…If the selected study did not include a risk estimate, we calculated the unadjusted RR and the 95% CI from the raw data for simplicity [16,17,23,24,[48][49][50][51]. Estimates were pooled using a random-effects model to calculate the summarized RRs and 95% CI [52][53][54]. If the selected studies reported the results of cardiovascular malformations as other outcomes but with similar definitions [e.g., congenital heart defect (CHD) or cardiac malformations], we combined the risk estimate to calculate the summarized RR of cardiovascular malformation.…”
Section: Discussionmentioning
confidence: 99%
“…Random‐effects models by DerSimonian and Laird were applied to obtain summarized OR estimates across the included studies. We calculated the I 2 statistic to quantify the magnitude between‐study heterogeneity, and assigned values of 50% or less, 51%–75%, and 76% or more for low‐, moderate‐ and high‐ heterogeneity, respectively . Subgroup analysis was carried out based on geographic location (Europe, North America and other regions).…”
Section: Methodsmentioning
confidence: 99%
“…Cancer patients with comorbidities have poorer survival and often do not receive various standard cancer and supportive-care therapies. [9][10][11] The impact of cancer and preexisting comorbidities on patients' symptom burden is only beginning to be appreciated. Although a few studies have highlighted the impact of multimorbidity on the receipt of cancer treatment, 12 fatigue and pain symptoms, 13 and mortality, 14 data on how comorbidity influences a patient's illness experience and overall symptom burden are sparse.…”
Section: Introductionmentioning
confidence: 99%