scholarly journals Factor Structure of the Gotland Scale of Male Depression in Two Samples of Men With Prostate Cancer

2016 ◽  
Vol 11 (1) ◽  
pp. 170-175 ◽  
Author(s):  
Christopher F. Sharpley ◽  
Vicki Bitsika ◽  
David R. H. Christie ◽  
Myra S. Hunter
Keyword(s):  
Prostate Cancer ◽  
Factor Structure ◽  
Clinical Settings ◽  
Treatment Needs ◽  
Male Depression ◽  
The United Kingdom ◽  
Two Samples ◽  
Significant Depression ◽  
Australian Sample ◽  
Clinically Significant

Up to a quarter of all prostate cancer (PCa) patients suffer from clinically significant depression but treatments are inconsistent and short-lived in their efficacy. One possible reason could be that “male depression” is not adequately diagnosed by the criteria for major depressive disorder (MDD) used in many clinical settings. In response to this limitation, the Gotland Scale of Male Depression (GSMD) was developed to identify the extra symptoms of MDD in men. Although the factor structure of the GSMD has been reported in non-PCa samples, it has not been determined for this group of men. Two samples of PCa patients were recruited, 191 from Australia and 138 from the United Kingdom and all patients received the GSMD individually, plus a background questionnaire. Two-factor solutions were identified for each of the two samples. The Australian sample was characterized by changes in emotional and somatic function, followed by depressed mood. The U.K. sample exhibited the same two-factor solution but in reverse order of weighting. Targeted treatments for depression in PCa patients may benefit from identification of the loadings that individual patients have on these two GSMD factors so that specific clinical profiles and treatment needs may be based on this information about their depression.

scholarly journals Psychological morbidity associated with prostate cancer: Rates and predictors of depression in the RADICAL PC study

2020 ◽  
Vol 15 (6) ◽  
Author(s):  
Gagan Fervaha ◽  
Jason P. Izard ◽  
Dean A. Tripp ◽  
Nazanin Aghel ◽  
Bobby Shayegan ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Performance Status ◽  
Survival Rates ◽  
Current Smoker ◽  
Multivariable Logistic Regression Model ◽  
High Risk Prostate Cancer ◽  
Patient Health ◽  
Significant Depression ◽  
Clinically Significant ◽  
Predictors Of Depression

Introduction: Across all cancer sites and stages, prostate cancer has one of the greatest median five-year survival rates, highlighting the important focus on survivorship issues following diagnosis and treatment. In the current study, we sought to evaluate the prevalence and predictors of depression in a large, multicenter, contemporary, prospectively collected sample of men with prostate cancer. Methods: Data from the current study were drawn from the baseline visit of men enrolled in the RADICAL PC study. Men with a new diagnosis of prostate cancer or patients initiating androgen deprivation therapy for prostate cancer for the first time were recruited. Depressive symptoms were evaluated using the nine-item version of the Patient Health Questionnaire (PHQ-9). To evaluate factors associated with depression, a multivariable logistic regression model was constructed, including biological, psychological, and social predictor variables. Results: Data from 2445 patients were analyzed. Of these, 201 (8.2%) endorsed clinically significant depression. Younger age (odds ratio [OR] 1.38; 95% confidence interval [CI] 1.16–1.60 per 10-year decrease), being a current smoker (OR 2.77; 95% CI 1.66–4.58), former alcohol use (OR 2.63; 95% CI 1.33–5.20), poorer performance status (OR 5.01; 95% CI 3.49–7.20), having a pre-existing clinical diagnosis of depression or anxiety (OR 3.64; 95% CI 2.42–5.48), and having high-risk prostate cancer (OR 1.49; 95% CI 1.05–2.12) all conferred independent risk for depression. Conclusions: Clinically significant depression is common in men with prostate cancer. Depression risk is associated with a host of biopsychosocial variables. Clinicians should be vigilant to screen for depression in those patients with poor social determinants of health, concomitant disability, and advanced disease.

Development and Psychometric Evaluation of a Revised Sense of Coherence Scale

2018 ◽  
Vol 34 (3) ◽  
pp. 206-215 ◽  
Author(s):  
Rahel Bachem ◽  
Andreas Maercker
Keyword(s):  
Posttraumatic Growth ◽  
Factor Structure ◽  
Sense Of Coherence ◽  
Psychological Health ◽  
Psychometric Evaluation ◽  
Health Indicators ◽  
Structure Stability ◽  
Confirmatory Factor Analyses ◽  
Reliability Factor ◽  
Two Samples

Abstract. The present study introduces a revised Sense of Coherence (SOC) scale, a new conceptualization and operationalization of the resilience indicator SOC. It outlines the scale development and aims for testing its reliability, factor structure, and validity. Literature on Antonovsky’s SOC (SOC-A) was critically reviewed to identify needs for improving the scale. The scale was investigated in two samples. Sample 1 consisted of 334 bereaved participants, Sample 2 of 157 healthy controls. The revised SOC Scale, SOC-A, and theoretically relevant questionnaires were applied. Explorative and confirmatory factor analyses established a three-factor structure in both samples. The revised SOC Scale showed significant but discriminative associations with related constructs, including self-efficacy, posttraumatic growth, and neuroticism. The revised measure was significantly associated with psychological health indicators, including persistent grief, depression, and anxiety, but not to the extent as the previous SOC-A. Stability over time was sufficient. The study provides psychometric support for the revised SOC conceptualization and scale. It has several advantages over the previous SOC-A scale (unique variance, distinct factor structure, stability). The scale could be used for clinical and health psychological testing or research into the growing field of studies on resilience over the life span.

754 Insomnia and Depression Symptoms in Primary Care Patients Referred for Mental Health Care

SLEEP ◽  
2021 ◽  
Vol 44 (Supplement_2) ◽  
pp. A294-A294
Author(s):  
Ivan Vargas ◽  
Alexandria Muench ◽  
Mark Seewald ◽  
Cecilia Livesey ◽  
Matthew Press ◽  
...  
Keyword(s):  
Mental Health ◽  
Primary Care ◽  
Health Care ◽  
Mental Health Care ◽  
Primary Care Providers ◽  
Depression Symptoms ◽  
Care Providers ◽  
Mild Depression ◽  
Significant Depression ◽  
Clinically Significant

Abstract Introduction Past epidemiological research indicates that insomnia and depression are both highly prevalent and tend to co-occur in the general population. The present study further assesses this association by estimating: (1) the concurrence rates of insomnia and depression in outpatients referred by their primary care providers for mental health care; and (2) whether the association between depression and insomnia varies by insomnia subtype (initial, middle, and late). Methods Data were collected from 3,174 patients (mean age=42.7; 74% women; 50% Black) who were referred to the integrated care program for assessment of mental health symptoms (2018–2020). All patients completed an Insomnia Severity Index (ISI) and a Patient Health Questionnaire (PHQ-9) during their evaluations. Total scores for the ISI and PHQ-9 were computed. These scores were used to categorize patients into diagnostic groups for insomnia (no-insomnia [ISI < 8], subthreshold-insomnia [ISI 8–14], and clinically-significant-insomnia [ISI>14]) and depression (no-depression [PHQ-914]). Items 1–3 of the ISI were also used to assess the association between depression and subtypes of insomnia. Results Rates of insomnia were as follows: 34.6% for subthreshold-insomnia, 35.5% for clinically-significant insomnia, and 28.9% for mild-depression and 26.9% for clinically-significant-depression. 92% of patients with clinically significant depression reported at least subthreshold levels of insomnia. While the majority of patients with clinical depression reported having insomnia, the proportion of patients that endorsed these symptoms were comparable across insomnia subtypes (percent by subtype: initial insomnia 63%; middle insomnia 61%; late insomnia 59%). Conclusion According to these data, the proportion of outpatients referred for mental health evaluations that endorse treatable levels of insomnia is very high (approximately 70%). This naturally gives rise to at least two questions: how will such symptomatology be addressed (within primary or specialty care) and what affect might targeted treatment for insomnia have on health were it a focus of treatment in general? Support (if any) Vargas: K23HL141581; Perlis: K24AG055602

scholarly journals Study protocol for a single-centre non-inferior randomised controlled trial on a novel three-dimensional matrix positioning-based cognitive fusion-targeted biopsy and software-based fusion-targeted biopsy for the detection rate of clinically significant prostate cancer in men without a prior biopsy

BMJ Open ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. e041427
Author(s):  
Biming He ◽  
Rongbing Li ◽  
Dongyang Li ◽  
Liqun Huang ◽  
Xiaofei Wen ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Detection Rate ◽  
Three Dimensional ◽  
Multiparametric Mri ◽  
Fusion Method ◽  
Targeted Biopsy ◽  
Cognitive Fusion ◽  
Single Centre ◽  
Clinically Significant ◽  
Randomised Controlled

IntroductionThe classical pathway for diagnosing prostate cancer is systematic 12-core biopsy under the guidance of transrectal ultrasound, which tends to underdiagnose the clinically significant tumour and overdiagnose the insignificant disease. Another pathway named targeted biopsy is using multiparametric MRI to localise the tumour precisely and then obtain the samples from the suspicious lesions. Targeted biopsy, which is mainly divided into cognitive fusion method and software-based fusion method, is getting prevalent for its good performance in detecting significant cancer. However, the preferred targeted biopsy technique in detecting clinically significant prostate cancer between cognitive fusion and software-based fusion is still beyond consensus.Methods and analysisThis trial is a prospective, single-centre, randomised controlled and non-inferiority study in which all men suspicious to have clinically significant prostate cancer are included. This study aims to determine whether a novel three-dimensional matrix positioning cognitive fusion-targeted biopsy is non-inferior to software-based fusion-targeted biopsy in the detection rate of clinically significant cancer in men without a prior biopsy. The main inclusion criteria are men with elevated serum prostate-specific antigen above 4–20 ng/mL or with an abnormal digital rectal examination and have never had a biopsy before. A sample size of 602 participants allowing for a 10% loss will be recruited. All patients will undergo a multiparametric MRI examination, and those who fail to be found with a suspicious lesion, with the anticipation of half of the total number, will be dropped. The remaining participants will be randomly allocated to cognitive fusion-targeted biopsy (n=137) and software-based fusion-targeted biopsy (n=137). The primary outcome is the detection rate of clinically significant prostate cancer for cognitive fusion-targeted biopsy and software-based fusion-targeted biopsy in men without a prior biopsy. The clinically significant prostate cancer will be defined as the International Society of Urological Pathology grade group 2 or higher.Ethics and disseminationEthical approval was obtained from the ethics committee of Shanghai East Hospital, Tongji University School of Medicine, Shanghai, China. The results of the study will be disseminated and published in international peer-reviewed journals.Trial registration numberClinicalTrials.gov Registry (NCT04271527).

Naive patients with suspicious prostate cancer and positive multiparametric magnetic resonance imaging (mp-MRI): is it time for fusion target biopsy alone?

2021 ◽  
pp. 205141582110237
Author(s):  
Enrico Checcucci ◽  
Sabrina De Cillis ◽  
Daniele Amparore ◽  
Diletta Garrou ◽  
Roberta Aimar ◽  
...  
Keyword(s):  
Magnetic Resonance Imaging ◽  
Prostate Cancer ◽  
Magnetic Resonance ◽  
Detection Rate ◽  
Resonance Imaging ◽  
Fusion Biopsy ◽  
Grade Group ◽  
Final Pathology ◽  
Multiparametric Magnetic Resonance Imaging ◽  
Clinically Significant

Objectives: To determine if standard biopsy still has a role in the detection of prostate cancer or clinically significant prostate cancer in biopsy-naive patients with positive multiparametric magnetic resonance imaging. Materials and methods: We extracted, from our prospective maintained fusion biopsy database, patients from March 2014 to December 2018. The detection rate of prostate cancer and clinically significant prostate cancer and complication rate were analysed in a cohort of patients who underwent fusion biopsy alone (group A) or fusion biopsy plus standard biopsy (group B). The International Society of Urological Pathology grade group determined on prostate biopsy with the grade group determined on final pathology among patients who underwent radical prostatectomy were compared. Results: Prostate cancer was found in 249/389 (64.01%) and 215/337 (63.8%) patients in groups A and B, respectively ( P=0.98), while the clinically significant prostate cancer detection rate was 57.8% and 55.1% ( P=0.52). No significant differences in complications were found. No differences in the upgrading rate between biopsy and final pathology finding after radical prostatectomy were recorded. Conclusions: In biopsy-naive patients, with suspected prostate cancer and positive multiparametric magnetic resonance imaging the addition of standard biopsy to fusion biopsy did not increase significantly the detection rate of prostate cancer or clinically significant prostate cancer. Moreover, the rate of upgrading of the cancer grade group between biopsy and final pathology was not affected by the addition of standard biopsy. Level of evidence: Not applicable for this multicentre audit.

scholarly journals Evaluation of the Ginsburg Scheme: Where Is Significant Prostate Cancer Missed?

Cancers ◽  
2021 ◽  
Vol 13 (10) ◽  
pp. 2502
Author(s):  
August Sigle ◽  
Cordula A. Jilg ◽  
Timur H. Kuru ◽  
Nadine Binder ◽  
Jakob Michaelis ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Logistic Regression ◽  
Regression Analysis ◽  
Cancer Detection ◽  
Logistic Regression Analysis ◽  
Anterior Region ◽  
Targeted Biopsy ◽  
Detection Rates ◽  
Clinically Significant ◽  
Systematic Biopsy

Background: Systematic biopsy (SB) according to the Ginsburg scheme (GBS) is widely used to complement MRI-targeted biopsy (MR-TB) for optimizing the diagnosis of clinically significant prostate cancer (sPCa). Knowledge of the GBS’s blind sectors where sPCa is missed is crucial to improve biopsy strategies. Methods: We analyzed cancer detection rates in 1084 patients that underwent MR-TB and SB. Cancerous lesions that were missed or underestimated by GBS were re-localized onto a prostate map encompassing Ginsburg sectors and blind-sectors (anterior, central, basodorsal and basoventral). Logistic regression analysis (LRA) and prostatic configuration analysis were applied to identify predictors for missing sPCa with the GBS. Results: GBS missed sPCa in 39 patients (39/1084, 3.6%). In 27 cases (27/39, 69.2%), sPCa was missed within a blind sector, with 17/39 lesions localized in the anterior region (43.6%). Neither LRA nor prostatic configuration analysis identified predictors for missing sPCa with the GBS. Conclusions: This is the first study to analyze the distribution of sPCa missed by the GBS. GBS misses sPCa in few men only, with the majority localized in the anterior region. Adding blind sectors to GBS defined a new sector map of the prostate suited for reporting histopathological biopsy results.

scholarly journals The Primacy of High B-Value 3T-DWI Radiomics in the Prediction of Clinically Significant Prostate Cancer

Diagnostics ◽  
2021 ◽  
Vol 11 (5) ◽  
pp. 739
Author(s):  
Alessandro Bevilacqua ◽  
Margherita Mottola ◽  
Fabio Ferroni ◽  
Alice Rossi ◽  
Giampaolo Gavelli ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Quantitative Imaging ◽  
B Value ◽  
Support Vector ◽  
Svm Classifier ◽  
Primary Role ◽  
High B Value ◽  
Wilcoxon Rank Sum Test ◽  
Apparent Diffusion ◽  
Clinically Significant

Predicting clinically significant prostate cancer (csPCa) is crucial in PCa management. 3T-magnetic resonance (MR) systems may have a novel role in quantitative imaging and early csPCa prediction, accordingly. In this study, we develop a radiomic model for predicting csPCa based solely on native b2000 diffusion weighted imaging (DWIb2000) and debate the effectiveness of apparent diffusion coefficient (ADC) in the same task. In total, 105 patients were retrospectively enrolled between January–November 2020, with confirmed csPCa or ncsPCa based on biopsy. DWIb2000 and ADC images acquired with a 3T-MRI were analyzed by computing 84 local first-order radiomic features (RFs). Two predictive models were built based on DWIb2000 and ADC, separately. Relevant RFs were selected through LASSO, a support vector machine (SVM) classifier was trained using repeated 3-fold cross validation (CV) and validated on a holdout set. The SVM models rely on a single couple of uncorrelated RFs (ρ < 0.15) selected through Wilcoxon rank-sum test (p ≤ 0.05) with Holm–Bonferroni correction. On the holdout set, while the ADC model yielded AUC = 0.76 (95% CI, 0.63–0.96), the DWIb2000 model reached AUC = 0.84 (95% CI, 0.63–0.90), with specificity = 75%, sensitivity = 90%, and informedness = 0.65. This study establishes the primary role of 3T-DWIb2000 in PCa quantitative analyses, whilst ADC can remain the leading sequence for detection.

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