Whole-genome and transcriptome analysis enhances precision cancer treatment options.

BACKGROUND: Recent advances are enabling delivery of precision genomic medicine to cancer clinics. While the majority of approaches profile panels of selected genes or hotspot regions, comprehensive data provided by whole-genome and transcriptome sequencing and analysis (WGTA) present an opportunity to align a much larger proportion of patients to therapies. PATIENTS AND METHODS: Samples from 570 patients with advanced or metastatic cancer of diverse types enrolled in the Personalized OncoGenomics (POG) program underwent WGTA. DNA-based data, including mutations, copy number and mutation signatures, were combined with RNA-based data, including gene expression and fusions, to generate comprehensive WGTA profiles. A multidisciplinary molecular tumour board used WGTA profiles to identify and prioritize clinically actionable alterations and inform therapy. Patient responses to WGTA-informed therapies were collected. RESULTS: Clinically actionable targets were identified for 83% of patients, of which 37% of patients received WGTA-informed treatments. RNA expression data were particularly informative, contributing to 67% of WGTA-informed treatments; 25% of treatments were informed by RNA expression alone. Of a total 248 WGTA-informed treatments, 46% resulted in clinical benefit. RNA expression data were comparable to DNA-based mutation and copy number data in aligning to clinically beneficial treatments. Genome signatures also guided therapeutics including platinum, poly-ADP ribose polymerase inhibitors and immunotherapies. Patients accessed WGTA-informed treatments through clinical trials (19%), off-label use (35%) and as standard therapies (46%) including those which would not otherwise have been the next choice of therapy, demonstrating the utility of genomic information to direct use of chemotherapies as well as targeted therapies. CONCLUSIONS: Integrating RNA expression and genome data illuminated treatment options that resulted in 46% of treated patients experiencing positive clinical benefit, supporting the use of comprehensive WGTA profiling in clinical cancer care.

Cost-effectiveness of brentuximab vedotin in advanced stage Hodgkin's lymphoma: a probabilistic analysis.

BACKGROUND: Treatment with ABVD (doxorubicin, bleomycin, vinblastine, and dacarbazine) is a well-established therapy for advanced Hodgkin's lymphoma (HL). However, the recently completed ECHELON-1 trial showed potential net clinical benefit for brentuximab vedotin (BREN+AVD) compared to ABVD as frontline therapy in patients with advanced Hodgkin's lymphoma. The objective of this analysis is to determine whether, on current evidence, BREN+AVD is cost-effective relative to ABVD as frontline therapy in patients with advanced HL. METHODS: We constructed a probabilistic Markov model with two arms and six mutually exclusive health states, using six-month cycle lengths, and a 15-year time horizon. Time-dependent transition probabilities were calculated from 'real-world' data collected by the BC Cancer's Centre for Lymphoid Cancer database or from the literature for ABVD. Time-dependent transition probabilities for BREN+AVD were taken from the ECHELON-1 trial. We estimated the incremental cost and effects per patient of each therapy and calculated the incremental cost-effectiveness ratio (ICER). Costs were measured in 2018 Canadian dollars and effects measured in quality-adjusted life years (QALYs). A probabilistic analysis was used to generate a cost-effectiveness acceptability curve (CEAC). RESULTS: The incremental cost between standard therapy with ABVD and therapy with BREN+AVD was estimated to be $192,336. The regimen of BREN+AVD resulted in a small benefit in terms of QALYs (0.46 QALYs). The estimated ICER was $418,122 per QALY gained. The probabilistic analysis suggests very few (8%) simulations fall below $100,000 per QALY. Even at a threshold of $200,000 per QALY gained, there was only a 24% chance that BREN+AVD would be considered cost-effective. Sensitivity analyses evaluating price reductions for brentuximab showed that these reductions needed to be in excess of 70% for this regimen to be cost-effective at a threshold of $100,000 per QALY. CONCLUSIONS: There may be a clinical benefit associated with BREN+AVD, but on current evidence the benefit is not adequately substantive compared to ABVD therapy given the cost of brentuximab vedotin. Agencies responsible for making decisions about BREN+AVD as frontline therapy for patients with advanced HL should consider whether they are willing to implement this treatment given the current uncertainty and cost-benefit profile, or negotiate substantial price-reductions from the manufacturer should they choose to reimburse.

Real-world costing analysis for diffuse large B-cell lymphoma in British Columbia.

Introduction: Diffuse large B-cell lymphoma (dlbcl) accounts for 30%-40% of all non-Hodgkin lymphomas. Approximately 60% of patients are cured with standard treatment. Targeted treatments are being investigated and might improve disease outcomes; however, their effect on cancer drug budgets will be significant. For the present study, we conducted an analysis of real-world costs for dlbcl patients treated in British Columbia, useful for health care system planning. Methods: Patient records from a retrospective cohort of patients diagnosed with dlbcl in British Columbia during 2004-2013 were anonymously linked across multiple administrative data sources: systemic therapy, radiotherapy, hospitalizations, oncologist services, outpatient medications, and fee-for-service physician services. Using generalized linear modelling regression, time-dependent costs (in 2015 Canadian dollars) were estimated in 6-month intervals over a 5-year period. The inverse probability weighting method was applied to account for censored observations. Nonparametric bootstrapping was used to estimate standard errors for the mean cost at each time interval. Results: The cohort consisted of 678 patients (5-year overall survival: 67%). Mean age at diagnosis was 64 ± 14 years; median follow-up was 3.2 years. Mean total cost of care was highest in the first 6 months after diagnosis ($29,120; 95% confidence interval: $28,986 to $29,170) and after disease progression ($18,480; 95% confidence interval: $15,187 to $24,772). Systemic therapy and hospitalization costs were the largest cost drivers. At each time interval, costs were observed to be positively skewed. Conclusions: Our results depict real-world costs for the treatment of dlbcl patients with standard chop-r therapy. Cost-model parameters are also provided for economic modelling of dlbcl interventions.

A time-and-motion approach to micro-costing of high-throughput genomic assays.

BACKGROUND: Genomic technologies are increasingly used to guide clinical decision-making in cancer control. Economic evidence about the cost-effectiveness of genomic technologies is limited, in part because of a lack of published comprehensive cost estimates. In the present micro-costing study, we used a time-and-motion approach to derive cost estimates for 3 genomic assays and processes-digital gene expression profiling (gep), fluorescence in situ hybridization (fish), and targeted capture sequencing, including bioinformatics analysis-in the context of lymphoma patient management. METHODS: The setting for the study was the Department of Lymphoid Cancer Research laboratory at the BC Cancer Agency in Vancouver, British Columbia. Mean per-case hands-on time and resource measurements were determined from a series of direct observations of each assay. Per-case cost estimates were calculated using a bottom-up costing approach, with labour, capital and equipment, supplies and reagents, and overhead costs included. RESULTS: The most labour-intensive assay was found to be fish at 258.2 minutes per case, followed by targeted capture sequencing (124.1 minutes per case) and digital gep (14.9 minutes per case). Based on a historical case throughput of 180 cases annually, the mean per-case cost (2014 Canadian dollars) was estimated to be $1,029.16 for targeted capture sequencing and bioinformatics analysis, $596.60 for fish, and $898.35 for digital gep with an 807-gene code set. CONCLUSIONS: With the growing emphasis on personalized approaches to cancer management, the need for economic evaluations of high-throughput genomic assays is increasing. Through economic modelling and budget-impact analyses, the cost estimates presented here can be used to inform priority-setting decisions about the implementation of such assays in clinical practice.

Research planning for the future of psychiatric diagnosis.

More than 10 years prior to the anticipated 2013 publication of DSM-5, processes were set in motion to assess the research and clinical issues that would best inform future diagnostic classification of mental disorders. These efforts intended to identify the clinical and research needs within various populations, examine the current state of the science to determine the empirical evidence for improving criteria within and across disorders, and stimulate research in areas that could potentially provide evidence for change. In the second phase of the revision process, the American Psychiatric Institute for Research and Education (APIRE) recently completed the 5-year international series of 13 diagnostic conferences convened by APA/APIRE in collaboration with the World Health Organization and the National Institutes of Health (NIH), under a cooperative grant funded by the NIH. From these conferences, the DSM-5 Task Force and Work Groups have developed plans for potential revisions for DSM-5, including the incorporation of dimensional approaches within and across diagnostic groups to clarify heterogeneity, improve diagnostic validity, and enhance clinical case conceptualization. Use of dimensions for measurement-based care has been shown to be feasible in psychiatric and primary care settings and may inform monitoring of disorder threshold, severity, and treatment outcomes. The integration of dimensions with diagnostic categories represents an exciting and potentially transformative approach for DSM-5 to simultaneously address DSM-IV's clinical short-comings and create novel pathways for research in neurobiology, genetics, and psychiatric epidemiology.

Valuing the benefit of diagnostic testing for genetic causes of idiopathic developmental disability: willingness to pay from families of affected children.

Idiopathic developmental disability (DD) has been found to put significant psychological distress on families of children with DD. The cause of the disability, however, is unknown for up to one-half of the affected children. Chromosomal abnormalities identified by cytogenetic analysis are the most frequently recognized cause of DD, although they account for less than 10% of cases. Array genomic hybridization (AGH) is a new diagnostic tool that provides a much higher detection rate for chromosomal imbalance than conventional cytogenetic analysis. This increase in diagnostic capability comes at greater monetary costs, which provides an impetus for understanding how individuals value genetic testing for DD. This study estimated the willingness to pay (WTP) for diagnostic testing to find a genetic cause of DD from families of children with DD. A discrete choice experiment was used to obtain WTP values. When it was assumed that AGH resulted in twice as many diagnoses and a 1-week reduction in waiting time compared with conventional cytogenetic analysis, this study found that families were willing to pay up to CDN$1118 (95% confidence interval, $498-1788) for the expected benefit. These results support the conclusion that the introduction of AGH into the Canadian health care system may increase the perceived welfare of society, but future studies should examine the cost-benefit of AGH vs cytogenetic testing.

The DISC Predictive Scales (DPS): efficiently screening for diagnoses.

OBJECTIVE: To derive and test a series of brief diagnosis-specific scales to identify subjects who are at high probability of meeting diagnostic criteria and those who may safely be spared more extensive diagnostic inquiry. METHOD: Secondary data analysis of a large epidemiological data set (n = 1,286) produced a series of gate and contingent items for each diagnosis. Findings were replicated in a second retrospective analysis from a residential care sample (n = 884). The DISC Predictive Scales (DPS) were then used prospectively as a self-report questionnaire in two studies, in which parents (n = 128) and/or adolescents (n = 208) had subsequent diagnostic interviewing with the Diagnostic Interview Schedule for Children or the Schedule for Affective Disorders and Schizophrenia for School-Age Children. RESULTS: All analyses showed that gate item selection was valid and that any missed cases were due solely to inconsistent reports on the same questions. Screening performance of the full scales was shown to be good, and substantial reductions in scale length were not associated with significant changes in discriminatory power. CONCLUSIONS: The DPS can accurately determine subjects who can safely be spared further diagnostic inquiry in any diagnostic area. This has the potential to speed up structured diagnostic interviewing considerably. The full DPS can be used to screen accurately for cases of specific DSM-III-R disorders.

Risk behavior in a community sample of children and adolescents.

OBJECTIVES: First, to investigate whether there is covariation between risk behaviors, including suicidality, in a community probability sample of children and adolescents; and second, to investigate whether risk behavior is associated with selected potential correlates. METHOD: A sample of 9- to 17-year-old youths (N = 1,285) and their caretakers were interviewed in the Methods for the Epidemiology of Child and Adolescent Mental Disorders (MECA) Study. The risk behaviors were marijuana smoking, alcohol use, intercourse, fighting, cigarette smoking, and suicidal ideation/attempts. Relationships between the risk behaviors were described using odds ratios. Linear regression analyses of an index of risk behavior on the selected potential correlates of risk behavior were conducted. RESULTS: There were significant relationships between all pairs of risk behaviors. The score on the index of risk behavior was associated with stressors, lack of resources, family psychiatric disorder, psychopathology, and functional impairment. CONCLUSIONS: Clinicians should be alerted to the possibility of risk behaviors, especially in children and adolescents engaging in other risk behaviors and those with inadequate resources, stressors, functional impairment, or psychopathology.

Mental health service use by Americans with severe mental illnesses.

BACKGROUND: The aim of this study was to determine the patterns and determinants of service use in severely mentally ill persons drawn from the National Institute of Mental Health Epidemiological Catchment Area (ECA) program, a community-based epidemiologic survey. This information provides a baseline against which to track ongoing changes in the US mental health service system. METHODS: Severe mental illness (SMI) was defined according to US Senate Appropriations Committee guidelines. Comparisons were made with persons who had a mental disorder that did not meet these criteria (non-SMI). Sociodemographic factors, and 1-year volume and intensity of mental or addictive services use were determined. Differences between those who used services and those who did not were examined using logistic regression. RESULTS: Persons with SMI differed from persons with non-SMI in most sociodemographic characteristics. A higher proportion of persons with SMI used ambulatory services, but the mean number of visits per person did not differ from the non-SMI population. Persons with SMI comprised the bulk of hospital inpatients admitted during a 1-year period. Several significant sociodemographic determinants of service use were found, with different patterns for general medical and specialty service use, pointing out potential barriers to care. CONCLUSIONS: As health care reform measures continue to be debated, attention to the service needs of the severely mentally ill is of crucial importance. Pre-managed care (pre-1993) baseline service use benchmarks will be essential to assess the impact of managed care on access to care, particularly for the severely mentally ill. Periodic collection of epidemiologic data on prevalence and service use would thus greatly facilitate service planning and addressing barriers to receiving mental health services in this population.

The cost of access to mental health services in managed care.

Managed care has controlled the cost of specialty mental health services, but its impact on access to care is not well described. In a retrospective design, the study used empirical data to demonstrate a direct relationship between managed care plans' claims costs per member per month and the proportion of plan members who use specialty mental health services annually. Each increment of $1 per member per month in spending on claims was associated with a.9 percent increase in the proportion of enrollees receiving specialty mental health treatment. These data raise concerns that plans with low per-member per-month costs may unduly restrict access to specialty treatment.

Community diagnosis counts.

Because of such validity-research deficits and the ceiling on agreement between instruments imposed by less-than-perfect reliability characteristics of each instrument, it is not appropriate to assume that the semistructured clinician interview is more valid than the epidemiologic interview. The Baltimore ECA site is uniquely situated to address this issue by comparing the outcome of subjects identified with current depression in the 1982 clinical reappraisal interview with those identified by the DIS at the same time to see if the 13-year follow-up is similar to that found over 16 years by Murphy et al. Where do we go from here in improving our diagnostic criteria for DSM-V, constructing better diagnostic instruments, and conducting the next generation of epidemiologic studies? Certainly the categorical diagnostic criteria themselves, without a dimensional symptom level, are never used in clinical treatment trials. Hence the "clinical significance" criteria of significant distress or disability added to DSM-IV should be further refined, with the possible addition of "staging" of disorders. The objective would be to provide a better indication of treatment need and clinical prognosis as in current cancer diagnostic assessments. For epidemiologic studies, the addition of symptom scales and disability assessments to the traditional categorical diagnoses should be helpful in developing community measures of treatment need. Different methods of assessment may be useful for diagnoses in which an impaired perception of reality occurs, such as schizophrenia. With some of these adjustments, it should be feasible to "count" those with clinically significant diagnoses in the community, and thus improve the validity and clinical utility of our diagnoses for predicting clinical course and responsiveness to specific treatments.

Depressive and disruptive disorders and mental health service utilization in children and adolescents.

OBJECTIVE: To examine the relationship of depressive and disruptive disorders with patterns of mental health services utilization in a community sample of children and adolescents. METHOD: Data were from the NIMH Methods for the Epidemiology of Child and Adolescent Mental Disorders (MECA) Study. The sample consisted of 1,285 child (ages 9-17 years) and parent/guardian pairs. Data included child psychopathology (assessed by the Diagnostic Interview Schedule for Children), impairment, child need and use of mental health services, and family socioeconomic status. RESULTS: After adjusting for potential confounding factors, disruptive disorder was significantly associated with children's use of mental health services, but depressive disorder was not. For school-based services, no difference was found between the 2 types of disorders. Parents perceived greater need for mental health services for children with disruptive disorders than for those with depression. Conversely, depression was more related to children's perception of mental health service need than was disruptive disorder. CONCLUSIONS: The findings highlight the need for more effective ways to identify and refer depressed children to mental health professionals, the importance of improving school-based services to meet children's needs, and the necessity to better educate parents and teachers regarding the identification of psychiatric disorders, especially depression.

Psychiatric comorbidity among adolescents with substance use disorders: findings from the MECA Study.

OBJECTIVE: To investigate the extent to which adolescents in the community with current substance use disorders (SUD) experience co-occurring psychiatric disorders. METHOD: Diagnostic data were obtained from probability samples of 401 children and adolescents, aged 14 to 17 years, and their mothers/caretakers, who participated in the Methods for the Epidemiology of Child and Adolescent Mental Disorders (MECA) Study. RESULTS: The rates of mood and disruptive behavior disorders are much higher among adolescents with current SUD than among adolescents without SUD. Comparison with adult samples suggests that the rates of current comorbidity of SUD with psychiatric disorders are the same among adolescents as adults, and lower for lifetime disruptive disorders/antisocial personality disorder among adolescents than adults. CONCLUSIONS: The high rate of coexisting psychiatric disorders among adolescents with SUD in the community needs to be taken into account in prevention and treatment programs.

A comparison of federal definitions of severe mental illness among children and adolescents in four communities.

OBJECTIVE: Using data from an epidemiological survey, the study compared existing definitions of severe mental illness and serious emotional disturbance among children and adolescents to demonstrate the range of prevalence rates resulting from application of different definitions to the same population. METHODS: Three definitions of severe mental illness and serious emotional disturbance were applied to data from the Methods for the Epidemiology of Child and Adolescent Mental Disorders survey, with a sample of 1,285, conducted in 1991-1992 by the National Institute of Mental Health. The resulting proportions of cases identified, demographic characteristics, service use, and perceived need for services were compared. RESULTS: From 3 to 23 percent of the sampled youth met criteria for severe mental illness or serious emotional disturbance. From 40 percent to as many as 78 percent of the defined youth used a mental health service in the year before the survey. School and ambulatory specialty settings were used most frequently. Generally, more than half of the parents of children with severe mental illness or serious emotional disturbance thought that their child needed services. CONCLUSIONS: The prevalence and characteristics of severe mental illness and serious emotional disturbance among children are sensitive to the definition used and its operationalization. Care should be taken by policy makers and service planners to avoid either over- or underestimating the prevalence of impaired youth in need of intensive interventions.

Prevalence of anxiety disorders and their comorbidity with mood and addictive disorders.

BACKGROUND: The co-occurrence of anxiety disorders with other mental, addictive, and physical disorders has important implications for treatment and for prediction of clinical course and associated morbidity. METHOD: Cross-sectional and prospective data on 20,291 individuals from the Epidemiologic Catchment Area (ECA) study were analysed to determine one-month, current disorders, one-year incidence, and one-year and lifetime prevalence of anxiety, mood, and addictive disorders, and to identify the onset and offset of disorders within the one-year prospective period. RESULTS: Nearly half (47.2%) of those meeting lifetime criteria for major depression also have met criteria for a comorbid anxiety disorder. The average age of onset of any lifetime anxiety disorder (16.4 years) and social phobia (11.6 years) among those with major depression was much younger than the onset age for major depression (23.2 years) and panic disorder. CONCLUSIONS: Anxiety disorders, especially social and simple phobias, appear to have an early onset in adolescence with potentially severe consequences, predisposing those affected to greater vulnerability to major depression and addictive disorders.

McLean Hospital depression research facility: early-onset phobic disorders and adult-onset major depression.

BACKGROUND: This study explores the temporal relationship between anxiety and major depressive disorders in a cohort of patients with current major depression. METHOD: Current prevalence and lifetime history of specific anxiety disorders were assessed using the Structured Clinical Interview for DSM-III-R Diagnosis (SCID-P) in 85 patients with DSM-III-R major depression. Consensus DSM-III-R diagnoses were assigned by at least two psychiatrists or psychologists. RESULTS: Twenty-nine per cent met criteria for at least one current anxiety disorder and 34% had at least one anxiety disorder at some point in their lives. The mean (s.d.) age of onset of anxiety disorder in the depressed patients with comorbid social or simple phobia (15 (9) years) was significantly younger than was that of their major depression (25 (9) years). In contrast, the mean (s.d.) age of onset of anxiety in patients with comorbid panic or OCD (20 (8) years) was similar to that seen for their major depression (21 (9) years). In patients with major depression with comorbid anxiety disorders, both the social phobia (10 of 13) and simple phobia (4 of 4) were more commonly reported to start at least two years prior to their major depression in contrast to depressives with comorbid panic (3 of 10 subjects)-Fisher's exact test, P = 0.01. CONCLUSIONS: Early-onset social and simple phobias appear to be risk factors for later onset of major depression.

Disability and psychiatric disorders in an urban community: measurement, prevalence and outcomes.

BACKGROUND: The purpose of this analysis was to examine: (1) the prevalence of psychiatric disorders among disabled people, using seven different measures of disability; (2) variation in disability between and within psychiatric diagnostic categories; and (3) relationship of diagnosis and disability to health service utilization. METHOD: Data were drawn from Phase I and Phase II of the Eastern Baltimore Mental Health Survey, part of the Epidemiologic Catchment Area Program (ECA) conducted in 1980-1 to survey mental morbidity within the adult population. A total of 810 individuals received both a household interview and a standardized clinical psychiatric evaluation. Estimated prevalence rates were computed using appropriate survey sampling weights. RESULTS: Prevalence of disability ranged from 2.5 to 19.5%, varying with specific disability measure. Among those classified as disabled by any of the measures examined, 56 to 92% had a psychiatric disorder and serious chronic medical conditions were present in the majority of these cases (54 to 78%). Disability was expressed differently among the various diagnostic groups. Diagnostic category and disability were significant independent predictors of medical service utilization and receipt of disability payments. CONCLUSIONS: The majority of disabled adults living in the community have diagnosable psychiatric disorders, with the majority of these individuals suffering from significant chronic medical conditions as well, thus making co-morbidity the norm.

Limitations of diagnostic criteria and assessment instruments for mental disorders. Implications for research and policy.

During the past 2 decades, psychiatric epidemiological studies have contributed a rapidly growing body of scientific knowledge on the scope and risk factors associated with mental disorders in communities. Technological advances in diagnostic criteria specificity and community case-identification interview methods, which made such progress feasible, now face new challenges. Standardized methods are needed to reduce apparent discrepancies in prevalence rates between similar population surveys and to differentiate clinically important disorders in need of treatment from less severe syndromes. Reports of some significant differences in mental disorder rates from 2 large community surveys conducted in the United States--the Epidemiologic Catchment Area study and the National Comorbidity Survey--provide the basis for examining the stability of methods in this field. We discuss the health policy implications of discrepant and/or high prevalence rates for determining treatment need in the context of managed care definitions of "medical necessity."