Comparative effectiveness research: Using systematic reviews and meta-analyses to synthesize empirical evidence

The increased demand for evidence-based health care practices calls for comparative effectiveness research (CER), namely the generation and synthesis of research evidence to compare the benefits and harms of alternative methods of care. A significant contribution of CER is the systematic identification and synthesis of available research studies on a specific topic. The purpose of this article is to provide an overview of methodological issues pertaining to systematic reviews and meta-analyses to be used by investigators with the purpose of conducting CER. A systematic review or meta-analysis is guided by a research protocol, which includes (a) the research question, (b) inclusion and exclusion criteria with respect to the target population and studies, (c) guidelines for obtaining relevant studies, (d) methods for data extraction and coding, (e) methods for data synthesis, and (f) guidelines for reporting results and assessing for bias. This article presents an algorithm for generating evidence-based knowledge by systematically identifying, retrieving, and synthesizing large bodies of research studies. Recommendations for evaluating the strength of evidence, interpreting findings, and discussing clinical applicability are offered

Psychometric Testing of the Decisional Conflict Scale: Genetic Testing Hereditary Breast and Ovarian Cancer

BACKGROUND: Hereditary breast and ovarian cancer (HBOC) syndrome is attributed mostly to mutations in the Breast Cancer 1 and Breast Cancer 2 genes (BRCA1/2). Mutation carriers of BRCA1/2 genes have significantly higher risk for developing breast cancer compared with the general population (55%-85% vs. 12%) and for developing ovarian cancer (20%-60% vs. 1.5%). The availability of genetic testing enables mutation carriers to make informed decisions about managing their cancer risk (e.g., risk-reducing surgery). However, uptake of testing for HBOC among high-risk individuals is low, indicating the need to better understand and measure the decisional conflict associated with this process. OBJECTIVE: The aim of this study was to evaluate the reliability and validity of the modified Decisional Conflict Scale for use in decisions associated with genetic testing for HBOC. METHODS: This cross-sectional cohort study, recruited women who pursued genetic testing for HBOC in two genetic risk assessment clinics affiliated with a large comprehensive cancer center and one of their female relatives who did not pursue testing. The final sample consisted of 342 women who completed all 16 items of the Decisional Conflict Scale. The psychometric properties of the scale were assessed using tests of reliability and validity, including face, content, construct, contrast, convergent, divergent, and predictive validity. RESULTS: Factor analysis using principal axis factoring with oblimin rotation elicited a three-factor structure: (a) Lack of Knowledge About the Decision (α = .97), (b) Lack of Autonomy in Decision Making (α = .94), and (c) Lack of Confidence in Decision Making (α = .87). These factors explained 82% of the variance in decisional conflict about genetic testing. Cronbach's alpha coefficient was .96. DISCUSSION: The instrument is an important tool for researchers and healthcare providers working with women at risk for HBOC who are deciding whether genetic testing is the right choice for them

Interventions with family caregivers of cancer patients: meta-analysis of randomized trials

Family caregivers of cancer patients receive little preparation, information, or support to perform their caregiving role. However, their psychosocial needs must be addressed so they can maintain their own health and provide the best possible care to the patient. The purpose of this article is to analyze the types of interventions offered to family caregivers of cancer patients, and to determine the effect of these interventions on various caregiver outcomes. Meta-analysis was used to analyze data obtained from 29 randomized clinical trials published from 1983 through March 2009. Three types of interventions were offered to caregivers: psychoeducational, skills training, and therapeutic counseling. Most interventions were delivered jointly to patients and caregivers, but they varied considerably with regard to dose and duration. The majority of caregivers were female (64%) and Caucasian (84%), and ranged in age from 18 to 92 years (mean age, 55 years). Meta-analysis indicated that although these interventions had small to medium effects, they significantly reduced caregiver burden, improved caregivers' ability to cope, increased their self-efficacy, and improved aspects of their quality of life. Various intervention characteristics were also examined as potential moderators. Clinicians need to deliver research-tested interventions to help caregivers and patients cope effectively and maintain their quality of life

Individual and family characteristics associated with BRCA1/2 genetic testing in high‐risk families

Background Little is known about family members' interrelated decisions to seek genetic testing for breast cancer susceptibility. Methods The specific aims of this cross‐sectional, descriptive, cohort study were (i) to examine whether individual and family characteristics have a direct effect on women's decisions to use genetic testing for hereditary susceptibility to breast cancer and (ii) to explore whether family characteristics moderate the relationships between individual characteristics and the decision to use genetic testing. Participants were women (>18 years old) who (i) received genetic testing for hereditary breast cancer and who agreed to invite one of their female relatives into the study and (ii) female relatives who had NOT obtained genetic testing and were identified by pedigree analysis as having >10% chances of hereditary susceptibility to breast cancer. Results The final sample consisted of 168 English‐speaking, family dyads who completed self‐administered, mailed surveys with validated instruments. Multivariate conditional logistic regression analyses showed that the proposed model explained 62% of the variance in genetic testing. The factors most significantly associated with genetic testing were having a personal history of cancer; perceiving genetic testing to have more benefits than barriers; having greater family hardiness; and perceiving fewer negative consequences associated with a breast cancer diagnosis. No significant interaction effects were observed. Conclusions Findings suggest that both individual and family characteristics are associated with the decision to obtain genetic testing for hereditary breast cancer; hence, there is a need for interventions that foster a supportive family environment for patients and their high‐risk relatives. Copyright © 2012 John Wiley & Sons, Ltd.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/98211/1/pon3139.pd

Improving palliative care outcomes in remote and rural areas of LMICs through family caregivers: lessons from Kazakhstan

Approximately 60 million people require palliative care worldwide, and nearly 80% of them live in low- and middle-income countries (LMICs). Providing palliative care in remote and rural areas of LMICs requires special consideration to ensure equitable access to healthcare. This perspective aims to deliver pragmatic, context-oriented policy recommendations designed to improve palliative care outcomes in Kazakhstan by capitalizing on existing resources and considering its unique geopolitical and sociocultural context. With approximately half of the population in Kazakhstan residing in remote and rural regions, the provision of healthcare services – specifically palliative care – mandates particular attention to ensure equal access to high-quality care. To understand challenges of implementing palliative care in remote and rural regions of Kazakhstan and to propose tailored solutions, 29 key stakeholders, including family caregivers, health professionals, and palliative care administrators, were identified in five regions of Kazakhstan. The main challenges encountered by family caregivers include lack of palliative care skills, the need for home-based care from mobile services, and high out-of-pocket expenditures. The challenges highlighted by healthcare providers and administrators were the lack of formal education in palliative care, shortage of opioids, and limited societal awareness and state support. Based on challenges elaborated from stakeholders and existing literature in palliative care and family caregiving, this perspective advocates against replicating the strategies implemented in high-income countries. Family caregivers play a critical role in implementing affordable and efficient palliative care in resource-limited settings. Enhancing their competencies through digital training and increasing access to palliative care services through mobile teams are tailored and localized solutions that address specific challenges in Kazakhstan. It is postulated that these recommendations may find utility in other LMICs, potentially benefiting nearly 48 million individuals who require these services

Interventions with Family Caregivers of Cancer Patients: Meta-Analysis of Randomized Trials

Family caregivers of cancer patients receive little preparation, information, or support to carry out their caregiving role. However, their psychosocial needs must be addressed so they can maintain their own health and provide the best possible care to the patient. The purpose of this article was to analyze the types of interventions offered to family caregivers of cancer patients, and to determine the effect of these interventions on various caregiver outcomes. Meta-analysis was used to analyze data obtained from 29 randomized clinical trials, published from 1983 to March, 2009. Three types of interventions were offered to caregivers: psychoeducational, skills training, and therapeutic counseling. Most interventions were delivered jointly to patients and caregivers, but they varied considerably on dose and duration. The majority of caregivers was female (64%), Caucasian (84%), and ranged from 18 to 92 years of age (mean 55). Meta-analysis indicated that although these interventions had small to medium effects, they significantly reduced caregiver burden, improved caregivers’ ability to cope, increased their self-efficacy, and improved aspects of their quality of life. Various intervention characteristics were also examined as potential moderators. Clinicians need to deliver research-tested interventions to help caregivers and patients cope effectively and maintain their quality of life

The Communication Chain of Genetic Risk: Analyses of Narrative Data Exploring Proband-Provider and Proband-Family Communication in Hereditary Breast and Ovarian Cancer.

Low uptake of genetic services among members of families with hereditary breast and ovarian cancer (HBOC) suggests limitations of proband-mediated communication of genetic risk. This study explored how genetic information proceeds from healthcare providers to probands and from probands to relatives, from the probands' perspectives. Using a grounded-theory approach, we analyzed narrative data collected with individual interviews and focus groups from a sample of 48 women identified as carriers of HBOC-associated pathogenic variants from three linguistic regions of Switzerland. The findings describe the "communication chain", confirming the difficulties of proband-mediated communication. Provider-proband communication is impacted by a three-level complexity in the way information about family communication is approached by providers, received by probands, and followed-up by the healthcare system. Probands' decisions regarding disclosure of genetic risk are governed by dynamic and often contradictory logics of action, interconnected with individual and family characteristics, eventually compelling probands to engage in an arbitrating process. The findings highlight the relevance of probands' involvement in the communication of genetic risk to relatives, suggesting the need to support them in navigating the complexity of family communication rather than replacing them in this process. Concrete actions at the clinical and health system levels are needed to improve proband-mediated communication

Machine learning techniques for personalized breast cancer risk prediction : comparison with the BCRAT and BOADICEA models

Comprehensive breast cancer risk prediction models enable identifying and targeting women at high-risk, while reducing interventions in those at low-risk. Breast cancer risk prediction models used in clinical practice have low discriminatory accuracy (0.53-0.64). Machine learning (ML) offers an alternative approach to standard prediction modeling that may address current limitations and improve accuracy of those tools. The purpose of this study was to compare the discriminatory accuracy of ML-based estimates against a pair of established methods-the Breast Cancer Risk Assessment Tool (BCRAT) and Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm (BOADICEA) models.; We quantified and compared the performance of eight different ML methods to the performance of BCRAT and BOADICEA using eight simulated datasets and two retrospective samples: a random population-based sample of U.S. breast cancer patients and their cancer-free female relatives (N = 1143), and a clinical sample of Swiss breast cancer patients and cancer-free women seeking genetic evaluation and/or testing (N = 2481).; Predictive accuracy (AU-ROC curve) reached 88.28% using ML-Adaptive Boosting and 88.89% using ML-random forest versus 62.40% with BCRAT for the U.S. population-based sample. Predictive accuracy reached 90.17% using ML-adaptive boosting and 89.32% using ML-Markov chain Monte Carlo generalized linear mixed model versus 59.31% with BOADICEA for the Swiss clinic-based sample.; There was a striking improvement in the accuracy of classification of women with and without breast cancer achieved with ML algorithms compared to the state-of-the-art model-based approaches. High-accuracy prediction techniques are important in personalized medicine because they facilitate stratification of prevention strategies and individualized clinical management

Challenges for Developing Palliative Care Services in Resource- Limited Settings of Kazakhstan

Background: Approximately 40 million people in need of palliative care worldwide, while 80% of them live in low- and middle-income countries. Kazakhstan, a low-to middle-income country with a reforming healthcare system, is committed to improving quality and accessibility of care for its 100,000 terminal patients in need of palliative care.Policy Options and Recommendations: To join the group of countries where palliative care is available, accessible, and affordable, Kazakhstan must integrate palliative services into the mainstream healthcare system at all levels, from primary healthcare to hospices, and from major cities to remote villages. Based on the evidence thoroughly collected directly from the Ministry of Health, authors propose a feasible set of recommendations regarding palliative policy, paint relief, infrastructure, workforce, and education, which could be implemented in LMICs beyond Kazakhstan.Conclusion: This study presents an analysis of challenges, recent developments, and needs of palliative care in Kazakhstan, including funding, policy, workforce, education, and infrastructure, providing an evidence base and recommendations for future development of palliative care in Kazakhstan and in other LMICs