Search

Objective: Personalised care requires the identification of modifiable risk factors so that interventions can be implemented rapidly following a gynaecological cancer diagnosis. Our objective was to determine what pre-treatment factors are associated with quality of life (QOL) at baseline (pre-treatment) and 12 months., Methods: 1222 women with a confirmed diagnosis of endometrial, ovarian, cervical or vulvar cancer from 82 UK NHS hospitals agreed to complete questionnaires at baseline, three and 12 months. Questionnaires included measures of QOL, health, lifestyle, support and self-management. The primary outcome measure was QOL as measured by Quality of Life in Adult Cancer Survivors (QLACS). Sites provided clinical data at baseline, six and 12 months. Linear regression models were constructed to examine the association between baseline characteristics and QOL outcomes., Results: QOL declined between baseline and 3 months, followed by an improvement at 12 months. Baseline (pre-treatment) factors associated with worse QOL at both baseline and 12 months were depression, anxiety, living in a more deprived area and comorbidities which limit daily activities, whereas higher self-efficacy and age of 50+ years were associated with better QOL., Conclusions: Depression, anxiety and self-efficacy are modifiable risk factors that can impact on QOL. Screening for these, and assessment of whether comorbidities limit daily activities, should be incorporated in a holistic needs assessment and interventions to improve self-efficacy should be made available. Care can then be personalised from the outset to enable all women with a gynaecological cancer the opportunity to have the best QOL., (Copyright © 2022 The Authors. Published by Elsevier Inc. All rights reserved.)

Background: Fear of disease progression (FOP) is a rational concern for women with Ovarian Cancer (OC) and depression is also common. To date there have been no randomized trials assessing the impact of psychological intervention on depression and FOP in this patient group., Patients and Methods: Patients with primary or recurrent OC who had recently completed chemotherapy were eligible if they scored between 5 and 19 on the PHQ-9 depression and were randomized 1:1 to Intervention (3 standardized CBT-based sessions in the 6-12 weeks post-chemotherapy) or Control (standard of care). PHQ-9, FOP-Q-SF, EORTC QLQ C30 and OV28 questionnaires were then completed every 3 months for up to 2 years. The primary endpoint was change in PHQ-9 at 3 months. Secondary endpoints were change in other scores at 3 months and all scores at later timepoints., Results: 182 patients registered; 107 were randomized; 54 to Intervention and 53 to Control; mean age 59 years; 75 (70%) had completed chemotherapy for primary and 32 (30%) for relapsed OC and 67 patients completed both baseline and 3-month questionnaires. Improvement in PHQ-9 was observed for patients in both study arms at three months compared to baseline but there was no significant difference in change between Intervention and Control. A significant improvement on FOP-Q-SF scores was seen in the Intervention arm, whereas for those in the Control arm FOP-Q-SF scores deteriorated at 3 months (intervention effect = -4.4 (-7.57, -1.22), p-value = 0.008)., Conclusions: CBT-based psychological support provided after chemotherapy did not significantly alter the spontaneously improving trajectory of depression scores at three months but caused a significant improvement in FOP. Our findings call for the routine implementation of FOP support for ovarian cancer patients., Competing Interests: Declaration of Competing Interest The authors have no conflicts of interest to disclose., (Crown Copyright © 2021. Published by Elsevier Inc. All rights reserved.)

Objective: Clinical genetic testing is commercially available for rs61764370, an inherited variant residing in a KRAS 3' UTR microRNA binding site, based on suggested associations with increased ovarian and breast cancer risk as well as with survival time. However, prior studies, emphasizing particular subgroups, were relatively small. Therefore, we comprehensively evaluated ovarian and breast cancer risks as well as clinical outcome associated with rs61764370., Methods: Centralized genotyping and analysis were performed for 140,012 women enrolled in the Ovarian Cancer Association Consortium (15,357 ovarian cancer patients; 30,816 controls), the Breast Cancer Association Consortium (33,530 breast cancer patients; 37,640 controls), and the Consortium of Modifiers of BRCA1 and BRCA2 (14,765 BRCA1 and 7904 BRCA2 mutation carriers)., Results: We found no association with risk of ovarian cancer (OR=0.99, 95% CI 0.94-1.04, p=0.74) or breast cancer (OR=0.98, 95% CI 0.94-1.01, p=0.19) and results were consistent among mutation carriers (BRCA1, ovarian cancer HR=1.09, 95% CI 0.97-1.23, p=0.14, breast cancer HR=1.04, 95% CI 0.97-1.12, p=0.27; BRCA2, ovarian cancer HR=0.89, 95% CI 0.71-1.13, p=0.34, breast cancer HR=1.06, 95% CI 0.94-1.19, p=0.35). Null results were also obtained for associations with overall survival following ovarian cancer (HR=0.94, 95% CI 0.83-1.07, p=0.38), breast cancer (HR=0.96, 95% CI 0.87-1.06, p=0.38), and all other previously-reported associations., Conclusions: rs61764370 is not associated with risk of ovarian or breast cancer nor with clinical outcome for patients with these cancers. Therefore, genotyping this variant has no clinical utility related to the prediction or management of these cancers., (Copyright © 2015 Elsevier Inc. All rights reserved.)

Objective: Ovarian cancer is a hormone-related disease with a strong genetic basis. However, none of its high-penetrance susceptibility genes and GWAS-identified variants to date are known to be involved in hormonal pathways. Given the hypothesized etiologic role of gonadotropins, an assessment of how variability in genes involved in the gonadotropin signaling pathway impacts disease risk is warranted., Methods: Genetic data from 41 ovarian cancer study sites were pooled and unconditional logistic regression was used to evaluate whether any of the 2185 SNPs from 11 gonadotropin signaling pathway genes was associated with ovarian cancer risk. A burden test using the admixture likelihood (AML) method was also used to evaluate gene-level associations., Results: We did not find any genome-wide significant associations between individual SNPs and ovarian cancer risk. However, there was some suggestion of gene-level associations for four gonadotropin signaling pathway genes: INHBB (p=0.045, mucinous), LHCGR (p=0.046, high-grade serous), GNRH (p=0.041, high-grade serous), and FSHB (p=0.036, overall invasive). There was also suggestive evidence for INHA (p=0.060, overall invasive)., Conclusions: Ovarian cancer studies have limited sample numbers, thus fewer genome-wide susceptibility alleles, with only modest associations, have been identified relative to breast and prostate cancers. We have evaluated the majority of ovarian cancer studies with biological samples, to our knowledge, leaving no opportunity for replication. Using both our understanding of biology and powerful gene-level tests, we have identified four putative ovarian cancer loci near INHBB, LHCGR, GNRH, and FSHB that warrant a second look if larger sample sizes and denser genotype chips become available., (Copyright © 2014 Elsevier Inc. All rights reserved.)