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61.

Aims

To examine the influence of pre-existing psychiatric disorder on the choice of treatment in patients with gynaecological cancer.

Materials and methods

The analyses were based on all patients who underwent surgical treatment for endometrial, ovarian or cervical cancer who were registered in the Danish Gynecological Cancer Database in the years 2007–2014 (3059 patients with ovarian cancer, 5100 patients with endometrial cancer and 1150 with cervical cancer). Logistic regression model and Cox regression model, adjusted for relevant confounders, were used to estimate the effect of pre-existing psychiatric disorder on the course of cancer treatment. Our outcomes were (i) presurgical oncological treatment, (ii) macroradical surgery for patients with ovarian cancer, (iii) radiation/chemotherapy within 30 days and 100 days after surgery and (iv) time from surgery to first oncological treatment.

Results

In the group of patients with ovarian cancer, more patients with a psychiatric disorder received macroradical surgery versus patients without a psychiatric disorder, corresponding to an adjusted odds ratio of 1.24 (95% confidence interval 0.62–2.41) and the chance for having oncological treatment within 100 days was odds ratio = 1.26 (95% confidence interval 0.77–2.10). As for patients with endometrial cancer, all outcome estimates were close to unity. The adjusted odds ratio for oncological treatment within 30 days after surgery in patients with cervical cancer with a history of psychiatric disorder was 0.20 (95% confidence interval 0.03–1.54).

Conclusions

We did not find any significant differences in the treatment of ovarian and endometrial cancer in patients with pre-existing psychiatric diagnoses. When it comes to oncological treatment, we suggest that increased attention should be paid to patients with cervical cancer having a pre-existing psychiatric diagnosis.  相似文献   
62.
Lung - Diaphragmatic paralysis (DP) is an important cause of dyspnea with many underlying etiologies; however, frequently no cause is identified despite extensive investigation. We hypothesized...  相似文献   
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Ovarian cancer is the fourth most common cause of cancer-related death in women in the developed world, and one of the most heritable cancers. One of the most significant risk factors for epithelial ovarian cancer (EOC) is a family history of breast and/or ovarian cancer. Combined risk factors can be used in models to stratify risk of EOC, and aid in decisions regarding risk-reduction strategies. Germline pathogenic variants in EOC susceptibility genes including those involved in homologous recombination and mismatch repair pathways are present in approximately 22% to 25% of EOC. These genes are associated with an estimated lifetime risk of EOC of 13% to 60% for BRCA1 variants and 10% to 25% for BRCA2 variants, with lower risks associated with remaining genes. Genome-wide association studies have identified single nucleotide polymorphisms (SNPs) thought to explain an additional 6.4% of the familial risk of ovarian cancer, with 34 susceptibility loci identified to date. However, an unknown proportion of the genetic component of EOC risk remains unexplained. This review comprises an overview of individual genes and SNPs suspected to contribute to risk of EOC, and discusses use of a polygenic risk score to predict individual cancer risk more accurately.  相似文献   
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PurposeTwitter is an increasingly popular social media platform within the health care community. The objective of this analysis is to characterize the profile of radiation oncology–related tweets and Twitter users over the past 6 years.Methods and MaterialsUsing the web-based social media analytics platform Symplur Signals, we filtered tweets containing at least 1 of the following hashtags or key words: #radonc, #radiationoncology, "rad onc," or "radiation oncology." We evaluated radiation oncology–related Twitter activity between October 2014 and March 2020 for tweet frequency, tweet content, and individuals or groups posting tweets. We identified the most influential Twitter users contributing to radiation oncology–related tweets.ResultsFrom 2014 to 2020, the quarterly volume of radiation oncology–related tweets increased from 5027 to 29,763. Physicians contributed the largest growth in tweet volume. Academic radiation oncologists comprise 60% of the most influential Twitter accounts responsible for radiation oncology–related content. The number of radiation-oncology resident physicians on Twitter increased from 25 to 328 over the past 6 years, and 20% of radiation-oncology residency programs have a Twitter account. Seventy-one percent of radiation oncology–related tweets generated direct communication via mentions, and 59% of tweets contain links to external sources, including scientific articles.ConclusionsThe number of physicians contributing radiation oncology–related Twitter content has increased significantly in recent years. Academic radiation oncologists are the primary influencers of radiation oncology–related Twitter activity. Twitter is used by radiation oncologists to both professionally network and discuss findings related to the field. There remains the opportunity for radiation oncologists to broaden their audience on Twitter to encompass a more diverse community, including patients.  相似文献   
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