Artificially Induced Epithelial-Mesenchymal Transition in Surgical Subjects: Its Implications in Clinical and Basic Cancer Research

BACKGROUND: Surgical samples have long been used as important subjects for cancer research. In accordance with an increase of neoadjuvant therapy, biopsy samples have recently become imperative for cancer transcriptome. On the other hand, both biopsy and surgical samples are available for expression profiling for predicting clinical outcome by adjuvant therapy; however, it is still unclear whether surgical sample expression profiles are useful for prediction via biopsy samples, because little has been done about comparative gene expression profiling between the two kinds of samples. METHODOLOGY AND FINDINGS: A total of 166 samples (77 biopsy and 89 surgical) of normal and malignant lesions of the esophagus were analyzed by microarrays. Gene expression profiles were compared between biopsy and surgical samples. Artificially induced epithelial-mesenchymal transition (aiEMT) was found in the surgical samples, and also occurred in mouse esophageal epithelial cell layers under an ischemic condition. Identification of clinically significant subgroups was thought to be disrupted by the disorder of the expression profile through this aiEMT. CONCLUSION AND SIGNIFICANCE: This study will evoke the fundamental misinterpretation including underestimation of the prognostic evaluation power of markers by overestimation of EMT IN past cancer research, and will furnish some advice for the near future as follows: 1) Understanding how long the tissues were under an ischemic condition. 2) Prevalence of biopsy samples for in vivo expression profiling with low biases on basic and clinical research. 3) Checking cancer cell contents and normal- or necrotic-tissue contamination in biopsy samples for prevalence

Disclosure of cancer diagnosis and prognosis: a survey of the general public's attitudes toward doctors and family holding discretionary powers

BACKGROUND: This study aimed to ask a sample of the general population about their preferences regarding doctors holding discretionary powers in relation to disclosing cancer diagnosis and prognosis. METHODS: The researchers mailed 443 questionnaires to registered voters in a ward of Tokyo which had a socio-demographic profile similar to greater Tokyo's average and received 246 responses (response rate 55.5%). We describe and analysed respondents' attitudes toward doctors and family members holding discretionary powers in relation to cancer diagnoses disclose. RESULTS: Amongst respondents who wanted full disclosure about the diagnosis without delay, 117 (69.6 %) respondents agreed to follow the doctor's discretion, whilst 111 (66.1 %) respondents agreed to follow the family member's decision. For respondents who preferred to have the diagnosis and prognosis withheld, 59 (26.5 %) agreed to follow the doctor's decision, and 79 (35.3 %) of respondents agreed with following family member's wishes. CONCLUSIONS: The greater proportion of respondents wants or permits disclosure of cancer diagnosis and prognosis. In patients who reveal negative attitudes toward being given a cancer disclosure directly, alternative options exist such as telling the family ahead of the patient or having a discussion of the cancer diagnosis with the patient together with the family. It is recommended that health professionals become more aware about the need to provide patients with their cancer diagnosis and prognosis in a variety of ways

Development and evaluation of a risk algorithm predicting alcohol dependence after early onset of regular alcohol use

The ESEMeD project is funded by the European Commission (Contracts QLG5-1999-01042; SANCO 2004123 and EAHC 20081308). The Portuguese Mental Health Study was carried out by the Department of Mental Health, Faculty of Medical Sciences, NOVA University of Lisbon, with collaboration of the Portuguese Catholic University, and was funded by Champalimaud Foundation, Gulbenkian Foundation, Foundation for Science and Technology (FCT) and Ministry of Health.Aims: Likelihood of alcohol dependence (AD) is increased among people who transition to greater levels of alcohol involvement at a younger age. Indicated interventions delivered early may be effective in reducing risk, but could be costly. One way to increase cost-effectiveness would be to develop a prediction model that targeted interventions to the subset of youth with early alcohol use who are at highest risk of subsequent AD. Design: A prediction model was developed for DSM-IV AD onset by age 25 years using an ensemble machine-learning algorithm known as ‘Super Learner’. Shapley additive explanations (SHAP) assessed variable importance. Setting and Participants: Respondents reporting early onset of regular alcohol use (i.e. by 17 years of age) who were aged 25 years or older at interview from 14 representative community surveys conducted in 13 countries as part of WHO's World Mental Health Surveys. Measurements: The primary outcome to be predicted was onset of life-time DSM-IV AD by age 25 as measured using the Composite International Diagnostic Interview, a fully structured diagnostic interview. Findings: AD prevalence by age 25 was 5.1% among the 10 687 individuals who reported drinking alcohol regularly by age 17. The prediction model achieved an external area under the curve [0.78; 95% confidence interval (CI) = 0.74–0.81] higher than any individual candidate risk model (0.73–0.77) and an area under the precision-recall curve of 0.22. Overall calibration was good [integrated calibration index (ICI) = 1.05%]; however, miscalibration was observed at the extreme ends of the distribution of predicted probabilities. Interventions provided to the 20% of people with highest risk would identify 49% of AD cases and require treating four people without AD to reach one with AD. Important predictors of increased risk included younger onset of alcohol use, males, higher cohort alcohol use and more mental disorders. Conclusions: A risk algorithm can be created using data collected at the onset of regular alcohol use to target youth at highest risk of alcohol dependence by early adulthood. Important considerations remain for advancing the development and practical implementation of such models.publishersversionepub_ahead_of_prin

Development and evaluation of a risk algorithm predicting alcohol dependence after early onset of regular alcohol use

The ESEMeD project is funded by the European Commission (Contracts QLG5-1999-01042; SANCO 2004123 and EAHC 20081308). The Portuguese Mental Health Study was carried out by the Department of Mental Health, Faculty of Medical Sciences, NOVA University of Lisbon, with collaboration of the Portuguese Catholic University, and was funded by Champalimaud Foundation, Gulbenkian Foundation, Foundation for Science and Technology (FCT) and Ministry of Health.Aims: Likelihood of alcohol dependence (AD) is increased among people who transition to greater levels of alcohol involvement at a younger age. Indicated interventions delivered early may be effective in reducing risk, but could be costly. One way to increase cost-effectiveness would be to develop a prediction model that targeted interventions to the subset of youth with early alcohol use who are at highest risk of subsequent AD. Design: A prediction model was developed for DSM-IV AD onset by age 25 years using an ensemble machine-learning algorithm known as ‘Super Learner’. Shapley additive explanations (SHAP) assessed variable importance. Setting and Participants: Respondents reporting early onset of regular alcohol use (i.e. by 17 years of age) who were aged 25 years or older at interview from 14 representative community surveys conducted in 13 countries as part of WHO's World Mental Health Surveys. Measurements: The primary outcome to be predicted was onset of life-time DSM-IV AD by age 25 as measured using the Composite International Diagnostic Interview, a fully structured diagnostic interview. Findings: AD prevalence by age 25 was 5.1% among the 10 687 individuals who reported drinking alcohol regularly by age 17. The prediction model achieved an external area under the curve [0.78; 95% confidence interval (CI) = 0.74–0.81] higher than any individual candidate risk model (0.73–0.77) and an area under the precision-recall curve of 0.22. Overall calibration was good [integrated calibration index (ICI) = 1.05%]; however, miscalibration was observed at the extreme ends of the distribution of predicted probabilities. Interventions provided to the 20% of people with highest risk would identify 49% of AD cases and require treating four people without AD to reach one with AD. Important predictors of increased risk included younger onset of alcohol use, males, higher cohort alcohol use and more mental disorders. Conclusions: A risk algorithm can be created using data collected at the onset of regular alcohol use to target youth at highest risk of alcohol dependence by early adulthood. Important considerations remain for advancing the development and practical implementation of such models.publishersversionepub_ahead_of_prin

Proof-of-concept of a data-driven approach to estimate the associations of comorbid mental and physical disorders with global health-related disability

Objective: The standard method of generating disorder-specific disability scores has lay raters make rankings between pairs of disorders based on brief disorder vignettes. This method introduces bias due to differential rater knowledge of disorders and inability to disentangle the disability due to disorders from the disability due to comorbidities. Methods: We propose an alternative, data-driven, method of generating disorder-specific disability scores that assesses disorders in a sample of individuals either from population medical registry data or population survey self-reports and uses Generalized Random Forests(GRF) to predict global (rather than disorder-specific) disability assessed by clinician ratings or by survey respondent self-reports. This method also provides a principled basis for studying patterns and predictors of heterogeneity in disorder-specific disability. We illustrate this method by analyzing data for 16 disorders assessed in the World Mental Health Surveys(n=53,645).Results: Adjustments for comorbidity decreased estimates of disorder-specific disability substantially. Estimates were generally somewhat higher with GRF than conventional multivariable regression models. Heterogeneity was nonsignificant. Conclusions: The results show clearly that the proposed approach is practical, and that adjustment is needed for comorbidities to obtain accurate estimates of disorder-specific disability. Expansion to a wider range of disorders would likely find more evidence for heterogeneity

Socio-economic variations in the mental health treatment gap for people with anxiety, mood, and substance use disorders: results from the WHO World Mental Health (WMH) surveys

Abstract BACKGROUND: The treatment gap between the number of people with mental disorders and the number treated represents a major public health challenge. We examine this gap by socio-economic status (SES; indicated by family income and respondent education) and service sector in a cross-national analysis of community epidemiological survey data. METHODS: Data come from 16 753 respondents with 12-month DSM-IV disorders from community surveys in 25 countries in the WHO World Mental Health Survey Initiative. DSM-IV anxiety, mood, or substance disorders and treatment of these disorders were assessed with the WHO Composite International Diagnostic Interview (CIDI). RESULTS: Only 13.7% of 12-month DSM-IV/CIDI cases in lower-middle-income countries, 22.0% in upper-middle-income countries, and 36.8% in high-income countries received treatment. Highest-SES respondents were somewhat more likely to receive treatment, but this was true mostly for specialty mental health treatment, where the association was positive with education (highest treatment among respondents with the highest education and a weak association of education with treatment among other respondents) but non-monotonic with income (somewhat lower treatment rates among middle-income respondents and equivalent among those with high and low incomes). CONCLUSIONS: The modest, but nonetheless stronger, an association of education than income with treatment raises questions about a financial barriers interpretation of the inverse association of SES with treatment, although future within-country analyses that consider contextual factors might document other important specifications. While beyond the scope of this report, such an expanded analysis could have important implications for designing interventions aimed at increasing mental disorder treatment among socio-economically disadvantaged people

The Epidemiology of Alcohol Use Disorders Cross-Nationally: Findings from the World Mental Health Surveys

Background: Prevalences of Alcohol Use Disorders (AUDs) and Mental Health Disorders (MHDs) in many individual countries have been reported but there are few cross-national studies. The WHO World Mental Health (WMH) Survey Initiative standardizes methodological factors facilitating comparison of the prevalences and associated factors of AUDs in a large number of countries to identify differences and commonalities. Methods: Lifetime and 12-month prevalence estimates of DSM-IV AUDs, MHDs, and associations were assessed in the 29 WMH surveys using the WHO CIDI 3.0. Results: Prevalence estimates of alcohol use and AUD across countries and WHO regions varied widely. Mean lifetime prevalence of alcohol use in all countries combined was 80%, ranging from 3.8% to 97.1%. Combined average population lifetime and 12-month prevalence of AUDs were 8.6% and 2.2% respectively and 10.7% and 4.4% among non-abstainers. Of individuals with a lifetime AUD, 43.9% had at least one lifetime MHD and 17.9% of respondents with a lifetime MHD had a lifetime AUD. For most comorbidity combinations, the MHD preceded the onset of the AUD. AUD prevalence was much higher for men than women. 15% of all lifetime AUD cases developed before age 18. Higher household income and being older at time of interview, married, and more educated, were associated with a lower risk for lifetime AUD and AUD persistence. Conclusions: Prevalence of alcohol use and AUD is high overall, with large variation worldwide. The WMH surveys corroborate the wide geographic consistency of a number of well-documented clinical and epidemiological findings and patterns

Association of Cohort and Individual Substance Use With Risk of Transitioning to Drug Use, Drug Use Disorder, and Remission From Disorder: Findings From the World Mental Health Surveys

Importance: Limited empirical research has examined the extent to which cohort-level prevalence of substance use is associated with the onset of drug use and transitioning into greater involvement with drug use. Objective: To use cross-national data to examine time-space variation in cohort-level drug use to assess its associations with onset and transitions across stages of drug use, abuse, dependence, and remission. Design, Setting, and Participants: The World Health Organization World Mental Health Surveys carried out cross-sectional general population surveys in 25 countries using a consistent research protocol and assessment instrument. Adults from representative household samples were interviewed face-to-face in the community in relation to drug use disorders. The surveys were conducted between 2001 and 2015. Data analysis was performed from July 2017 to July 2018. Main Outcomes and Measures: Data on timing of onset of lifetime drug use, DSM-IV drug use disorders, and remission from these disorders was assessed using the Composite International Diagnostic Interview. Associations of cohort-level alcohol prevalence and drug use prevalence were examined as factors associated with these transitions. Results: Among the 90 027 respondents (48.1% [SE, 0.2%] men; mean [SE] age, 42.1 [0.1] years), 1 in 4 (24.8% [SE, 0.2%]) reported either illicit drug use or extramedical use of prescription drugs at some point in their lifetime, but with substantial time-space variation in this prevalence. Among users, 9.1% (SE, 0.2%) met lifetime criteria for abuse, and 5.0% (SE, 0.2%) met criteria for dependence. Individuals who used 2 or more drugs had an increased risk of both abuse (odds ratio, 5.17 [95% CI, 4.66-5.73]; P \u3c .001) and dependence (odds ratio, 5.99 [95% CI, 5.02-7.16]; P \u3c .001) and reduced probability of remission from abuse (odds ratio, 0.86 [95% CI, 0.76-0.98]; P = .02). Birth cohort prevalence of drug use was also significantly associated with both initiation and illicit drug use transitions; for example, after controlling for individuals’ experience of substance use and demographics, for each additional 10% of an individual’s cohort using alcohol, a person’s odds of initiating drug use increased by 28% (odds ratio, 1.28 [95% CI, 1.26-1.31]). Each 10% increase in a cohort’s use of drug increased individual risk by 12% (1.12 [95% CI, 1.11-1.14]). Conclusions and Relevance: Birth cohort substance use is associated with drug use involvement beyond the outcomes of individual histories of alcohol and other drug use. This has important implications for understanding pathways into and out of problematic drug use