Association of genetically-predicted placental gene expression with adult blood pressure traits.

OBJECTIVE: Blood pressure is a complex, polygenic trait, and the need to identify prehypertensive risks and new gene targets for blood pressure control therapies or prevention continues. We hypothesize a developmental origins model of blood pressure traits through the life course where the placenta is a conduit mediating genomic and nongenomic transmission of disease risk. Genetic control of placental gene expression has recently been described through expression quantitative trait loci (eQTL) studies which have identified associations with childhood phenotypes. METHODS: We conducted a transcriptome-wide gene expression analysis estimating the predicted gene expression of placental tissue in adult individuals with genome-wide association study (GWAS) blood pressure summary statistics. We constructed predicted expression models of 15 154 genes from reference placenta eQTL data and investigated whether genetically-predicted gene expression in placental tissue is associated with blood pressure traits using published GWAS summary statistics. Functional annotation of significant genes was generated using FUMA. RESULTS: We identified 18, 9, and 21 genes where predicted expression in placenta was significantly associated with systolic blood pressure (SBP), diastolic blood pressure (DBP), and pulse pressure (PP), respectively. There were 14 gene-tissue associations (13 unique genes) significant only in placenta. CONCLUSIONS: In this meta-analysis using S-PrediXcan and GWAS summary statistics, the predicted expression in placenta of 48 genes was statistically significantly associated with blood pressure traits. Notable findings included the association of FGFR1 expression with increased SBP and PP. This evidence of gene expression variation in placenta preceding the onset of adult blood pressure phenotypes is an example of extreme preclinical biological changes which may benefit from intervention.

Assessing patient-level knowledge of precision medicine in a community health center setting.

As precision medicine approaches are implemented, cancer treatment decisions have come to require comprehension of genetic tests and their role in risk stratification and treatment options. Acceptance and implementation of precision medicine requires patient understanding of numeracy, genetic literacy, health literacy, and medical trust. Implementing precision medicine in a US federally qualified community health center (FQCHC) setting has received little attention. Using a mixed-methods approach, we sought to identify patient-level factors influencing the understanding of cancer risk and precision medicine among FQCHC patients. We enrolled 26 English-speaking adults aged 40-79 years. Participants enrolled in focus groups and completed surveys to assess patient-level understanding of precision medicine, numeracy, and health literacy. The majority of participants were female (77%) and self-identified as African American (89%). Approximately one-third reported having a high school degree or less. While health literacy was generally high, 42% felt that genes or genetics had little impact on health and most (69%) reported little familiarity with precision medicine. Many participants reported that trust in their providers was extremely or very important when receiving genetic tests. Numeracy levels were moderate, with nearly half reporting some discomfort working with fractions and 38% finding numerical information only occasionally useful. Findings suggest that patients may lack familiarity with precision medicine concepts relevant for understanding cancer treatment decisions. Future educational efforts may help bridge the gap in patient understanding and facilitate equitable opportunities for precision medicine for all patients, including those seeking care from community health centers.

Development and Validation of the Perceptions of Research Trustworthiness Scale to Measure Trust Among Minoritized Racial and Ethnic Groups in Biomedical Research in the US.

Importance: Historically, trust in biomedical research has been lower among minoritized racial and ethnic groups who are underrepresented in and excluded from research, with the same groups experiencing worse health outcomes. Unfortunately, instruments that measure trust may not capture components of trust relevant to minoritized racial and ethnic groups. Objective: To develop and validate a scale to measure trust in biomedical research among minoritized racial and ethnic groups. Design, Setting, and Participants: This cross-sectional, community-based survey study compared trust and distrust in biomedical research among Black, Latino, and White subgroups in the US using the Perceptions of Research Trustworthiness (PoRT) scale. The scale was developed between March 22, 2016, and September 19, 2018, as part of this study, and its structure, reliability, and validity were examined during pilot (n = 381) and validation (n = 532) phases between February 4, 2019, and July 27, 2021. Convenience samples of adult participants (aged ≥18 years) were recruited locally (Nashville, Tennessee, and San Antonio, Texas) and nationally through the ResearchMatch and Cint online platforms. Main Outcomes and Measures: Overall and individual item Trust and Distrust subscale scores were compared. Overall Trust and Distrust scores were compared by race and ethnicity using a Kruskal-Wallis H test and individual item scores were compared using independent samples t test. Results: Of the 532 participants in the scale validation study, 144 (27.1%) were Black, 90 (16.9%) were Latino, and 282 (53.0%) were White. Participants had a median age of 43 years (range, 18-90 years), 352 (66.2%) were women, and 198 (37.2%) had educational attainment levels less than a college degree. Factor analysis of the 18-item PoRT scale revealed a 2-factor structure with two 9-item PoRT subscales (Trust and Distrust), which demonstrated high internal consistency (Cronbach α = 0.72 and 0.87, respectively). Mean (SD) Trust subscale scores were lower among Black (34.33 [2.02]) and Latino (34.55 [1.97]) participants compared with White participants (36.32 [1.81]; P < .001). Mean (SD) Distrust subscale scores were higher among Black (21.0 [2.15]) and Latino (20.53 [2.21]) participants compared with White participants (18.4 [2.03]; P < .001). Individual item results showed that Black and Latino participants were less trusting and more distrusting than White individuals on items related to risks, harms, secrecy, confidentiality, and privacy. Conclusions and Relevance: These findings suggest that the PoRT scale incorporates trust and trustworthiness concepts relevant among Black and Latino individuals and may allow more precise assessment of trust in research among these groups.

Development and pilot implementation of guidelines for culturally tailored research recruitment materials for African Americans and Latinos.

BACKGROUND: Previous studies support cultural tailoring of recruitment materials as a strategy to promote the enrollment of minoritized groups in clinical trials. However, there is a lack of guidance for research teams to create culturally tailored materials, potentially contributing to low recruitment rates of minoritized groups. We describe the development and pilot testing of recruitment material guidelines used to culturally tailor clinical trial recruitment materials targeting African Americans and Latinos. METHODS: The guideline development team consisted of investigators, research staff, and community leaders and members experienced in the recruitment and community engagement of minoritized groups. The recruitment material guidelines were developed using the literature, focus groups with African Americans and Latinos, the teams' research experience, and guidance from a community advisory board. To assess the effectiveness of the guidelines, a pilot study was conducted comparing advertisement click-through rates and enrollment outcomes between two institutions differing in use of culturally tailored versus non-tailored Facebook banner ads for the "Aspirin Dosing: A Patient-centric Trial Assessing Benefits and Long-Term Effectiveness" (ADAPTABLE) study. RESULTS: Five themes emerged from focus groups: (1) employ diversity and inclusion in recruitment efforts; (2) access multiple recruitment channels to increase reach and possible participation; (3) increase your "footwork"; (4) personalize outreach and recruitment to specific groups' beliefs and values; (5) align recruitment messaging with language preferences and motivations for study participation; and (6) specify incentives for participation. Guidelines were: 1) be inclusive; 2) use all forms of media; 3) take a personalized approach; 4) align recruitment messaging with motivations for study participation; 5) specify incentives; and 6) get out into the community. Additional guidelines were developed addressing specific considerations for images and language when targeting African American and Latino populations. Pilot study results demonstrated that clicks per impression ratio (0.47 clicks per impression vs. 0.03 clicks per impression) and the percentage of African American enrollment were significantly higher when using tailored compared to non-tailored ads (12.8% vs. 8.3%, respectively). CONCLUSION: The recruitment material guidelines offer practical recommendations to reach diverse populations for clinical trial participation more effectively. Our preliminary data supports use of these guidelines as a strategy to enhance recruitment of minoritized groups into clinical research studies.

Determinants of stage at diagnosis of HPV-related cancer including area deprivation and clinical factors.

BACKGROUND: Collecting social determinants of health in electronic health records is time-consuming. Meanwhile, an Area Deprivation Index (ADI) aggregates sociodemographic information from census data. The objective of this study was to ascertain whether ADI is associated with stage of human papillomavirus (HPV)-related cancer at diagnosis. METHODS: We tested for the association between the stage of HPV-related cancer presentation and ADI as well as the association between stage and the value of each census-based measure using ordered logistic regression, adjusting for age, race and sex. RESULTS: Among 3247 cases of HPV-related cancers presenting to an urban academic medical center, the average age at diagnosis was 57. The average stage at diagnosis was Surveillance, Epidemiology and End Results Stage 3. In the study population, 43% of patients were female and 87% were white. In this study population, there was no association between stage of HPV-related cancer presentation and either aggregate or individual census variables. CONCLUSIONS: These results may reflect insufficient sample size, a lack of socio-demographic diversity in our population, or suggest that simplifying social determinants of health into a single geocoded index is not a reliable surrogate for assessing a patient's risk for HPV-related cancer.

Design and implementation of a massive open online course on enhancing the recruitment of minorities in clinical trials - Faster Together.

BACKGROUND: Racial and ethnic minorities are often underrepresented in clinical trials, threatening the generalizability of trial results. Several factors may contribute to underrepresentation of minorities in clinical trials, including lack of training for researchers and staff on the importance of diversity in clinical trials and effective strategies for recruiting and retaining minority populations. METHODS: Applying community engaged research principles, we developed a massive open online course (MOOC) to help research team members develop knowledge and skills to enhance the recruitment of minorities in clinical trials. A transdisciplinary working group, consisting of clinical researchers, community engagement specialists, minority clinical trial recruitment and retention educators and specialists, and knowledge management information scientists, was formed to develop an evidence-based curriculum. Feedback from the Recruitment Innovation Center Community Advisory Board was incorporated to help finalize the curriculum. The course was implemented in Coursera, an online learning platform offering MOOCs. A bootstrap paired sample t-test was used to compare pre- and post-assessments of knowledge, attitudes, and intentions as it relates to minority recruitment. RESULTS: The final course, entitled Faster Together, was divided into eight 1-h modules. Each module included video presentations, reading assignments, and quizzes. After 10 months, 382 individuals enrolled in the course, 105 participants completed the pre-test, and 14 participants completed the post-test. Participants' knowledge scores were higher with an increase in the mean number of correct answers from 15.4 (95% CI:12.1-18.7) on the pre-test to 18.7 (95% CI:17.42-20.2) on the post-test. All post-test respondents (n = 14) indicated that the course improved their professional knowledge, and 71.4% of respondents indicated that they were very likely to make changes to their recruitment practices. CONCLUSIONS: Faster Together, a massive open online course, is an acceptable, accessible approach to educating research teams on minority recruitment in clinical trials. Preliminary evidence indicates the course increased knowledge on how to recruit minorities into clinical trials and could promote change in their recruitment practices.

Factors influencing precision medicine knowledge and attitudes.

Precision medicine holds great promise for improving health and reducing health disparities that can be most fully realized by advancing diversity and inclusion in research participants. Without engaging underrepresented groups, precision medicine could not only fail to achieve its promise but also further exacerbate the health disparities already burdening the most vulnerable. Yet underrepresentation by people of non-European ancestry continues in precision medicine research and there are disparities across racial groups in the uptake of precision medicine applications and services. Studies have explored possible explanations for population differences in precision medicine participation, but full appreciation of the factors involved is still developing. To better inform the potential for addressing health disparities through PM, we assessed the relationship of precision medicine knowledge and trust in biomedical research with sociodemographic variables. Using a series of linear regression models applied to survey data collected in a diverse sample, we analyzed variation in both precision medicine knowledge and trust in biomedical research with socioeconomic factors as a way to understand the range of precision medicine knowledge (PMK) in a broadly representative group and its relationship to trust in research and demographic characteristics. Our results demonstrate that identifying as Black, while significantly PMK, explains only 1.5% of the PMK variance in unadjusted models and 7% of overall variance in models adjusted for meaningful covariates such as age, marital status, employment, and education. We also found a positive association between PMK and trust in biomedical research. These results indicate that race is a factor affecting PMK, even after accounting for differences in sociodemographic variables. Additional work is needed, however, to identify other factors contributing to variation in PMK as we work to increase diversity and inclusion in precision medicine applications.

A taxonomy of impacts on clinical and translational research from community stakeholder engagement.

BACKGROUND: Community engagement is increasingly recognized as a valuable tool in clinical and translational research; however, the impact of engagement is not fully understood. No standard nomenclature yet exists to clearly define how research changes when community stakeholders are engaged across the research spectrum. This severely limits our ability to assess the value of community engagement in research. To address this gap, we developed a taxonomy for characterizing and classifying changes in research due to community engagement. METHODS: Using an iterative process, we (a) identified areas of potential impact associated with community engagement from author experience, (b) categorized these in taxonomic bins based on research stages, (c) conducted semi-structured interviews with researchers and community stakeholders, (d) validated the codebook in a sample dataset and (e) refined the taxonomy based on the validation. Community stakeholders were involved in every step of the process including as members of the primary study team. RESULTS: The final taxonomy catalogues changes into eleven domains corresponding to research phases. Each domain includes 2-4 dimensions depicting concepts within the domain's scope and, within each dimension, 2-10 elements labelling activities through which community engagement could change research. CONCLUSIONS: Community engagement has great potential to enhance clinical and translational research. This taxonomy provides a common vocabulary and framework for understanding the impact of community engagement and suggests metrics for assessing the value of community engagement in research.

Enrichment sampling for a multi-site patient survey using electronic health records and census data.

Objective: We describe a stratified sampling design that combines electronic health records (EHRs) and United States Census (USC) data to construct the sampling frame and an algorithm to enrich the sample with individuals belonging to rarer strata. Materials and Methods: This design was developed for a multi-site survey that sought to examine patient concerns about and barriers to participating in research studies, especially among under-studied populations (eg, minorities, low educational attainment). We defined sampling strata by cross-tabulating several socio-demographic variables obtained from EHR and augmented with census-block-level USC data. We oversampled rarer and historically underrepresented subpopulations. Results: The sampling strategy, which included USC-supplemented EHR data, led to a far more diverse sample than would have been expected under random sampling (eg, 3-, 8-, 7-, and 12-fold increase in African Americans, Asians, Hispanics and those with less than a high school degree, respectively). We observed that our EHR data tended to misclassify minority races more often than majority races, and that non-majority races, Latino ethnicity, younger adult age, lower education, and urban/suburban living were each associated with lower response rates to the mailed surveys. Discussion: We observed substantial enrichment from rarer subpopulations. The magnitude of the enrichment depends on the accuracy of the variables that define the sampling strata and the overall response rate. Conclusion: EHR and USC data may be used to define sampling strata that in turn may be used to enrich the final study sample. This design may be of particular interest for studies of rarer and understudied populations.

Development and validation of the Person-Centeredness of Research Scale.

AIM: Person-centeredness shifts the focus of healthcare and research to the needs and priorities of patients and communities, and may improve health outcomes. There are no instruments available, however, with which we can assess the degree to which research is indeed person-centered. Our aim was to develop and validate a quantitative instrument to rate person-centeredness of research. MATERIALS & METHODS: Scale development and validation entailed a multistep approach that led to the seven-item Person Centeredness of Research Scale (PCoR Scale) that uses a 5-point Likert rating scale. The scale was validated using ratings of the Patient-Centered Outcomes Research Institute-funded research abstracts or abstracts submitted to a translational science meeting. RESULTS: Psychometric properties of the PCoR Scale showed high internal consistency (α = 0.96). All seven items were highly correlated with the total score (rs range from 0.63 to 0.90). An exploratory factor analysis demonstrated that all of the items loaded on a single factor, explaining 80% of the variance. The Patient-Centered Outcomes Research Institute-funded research abstracts had a mean PCoR Scale score of 6.52 (±8.01) that was significantly higher than the abstracts submitted to the translational science meeting (-2.56 (±9.18); t = 8.09; p < 0.0001). Inter-rater reliability in the validation of the revised instrument was high (Intraclass Correlation Coefficient [ICC](group1) = 0.89; ICC(group2) = 0.95). CONCLUSION: This brief, quantitative rating scale is the first to assess the main constructs that describe person-centeredness of research products. The PCoR Scale can be used to assess person-centeredness in research products; for example, by funders evaluating proposals, data networks evaluating data requests or researchers evaluating their research designs.

A case study evaluating the portability of an executable computable phenotype algorithm across multiple institutions and electronic health record environments.

Electronic health record (EHR) algorithms for defining patient cohorts are commonly shared as free-text descriptions that require human intervention both to interpret and implement. We developed the Phenotype Execution and Modeling Architecture (PhEMA, http://projectphema.org) to author and execute standardized computable phenotype algorithms. With PhEMA, we converted an algorithm for benign prostatic hyperplasia, developed for the electronic Medical Records and Genomics network (eMERGE), into a standards-based computable format. Eight sites (7 within eMERGE) received the computable algorithm, and 6 successfully executed it against local data warehouses and/or i2b2 instances. Blinded random chart review of cases selected by the computable algorithm shows PPV ≥90%, and 3 out of 5 sites had >90% overlap of selected cases when comparing the computable algorithm to their original eMERGE implementation. This case study demonstrates potential use of PhEMA computable representations to automate phenotyping across different EHR systems, but also highlights some ongoing challenges.

Concordance between Research Sequencing and Clinical Pharmacogenetic Genotyping in the eMERGE-PGx Study.

There has been extensive debate about both the necessity of orthogonal confirmation of next-generation sequencing (NGS) results in Clinical Laboratory Improvement Amendments-approved laboratories and return of research NGS results to participants enrolled in research studies. In eMERGE-PGx, subjects underwent research NGS using PGRNseq and orthogonal targeted genotyping in clinical laboratories, which prompted a comparison of genotyping results between platforms. Concordance (percentage agreement) was reported for 4077 samples tested across nine combinations of research and clinical laboratories. Retesting was possible on a subset of 1792 samples, and local laboratory directors determined sources of genotype discrepancy. Research NGS and orthogonal clinical genotyping had an overall per sample concordance rate of 0.972 and per variant concordance rate of 0.997. Genotype discrepancies attributed to research NGS were because of sample switching (preanalytical errors), whereas the majority of genotype discrepancies (92.3%) attributed to clinical genotyping were because of allele dropout as a result of rare variants interfering with primer hybridization (analytical errors). These results highlight the analytical quality of clinically significant pharmacogenetic variants derived from NGS and reveal important areas for research and clinical laboratories to address with quality management programs.

Trans-ethnic Meta-analysis and Functional Annotation Illuminates the Genetic Architecture of Fasting Glucose and Insulin.

Knowledge of the genetic basis of the type 2 diabetes (T2D)-related quantitative traits fasting glucose (FG) and insulin (FI) in African ancestry (AA) individuals has been limited. In non-diabetic subjects of AA (n = 20,209) and European ancestry (EA; n = 57,292), we performed trans-ethnic (AA+EA) fine-mapping of 54 established EA FG or FI loci with detailed functional annotation, assessed their relevance in AA individuals, and sought previously undescribed loci through trans-ethnic (AA+EA) meta-analysis. We narrowed credible sets of variants driving association signals for 22/54 EA-associated loci; 18/22 credible sets overlapped with active islet-specific enhancers or transcription factor (TF) binding sites, and 21/22 contained at least one TF motif. Of the 54 EA-associated loci, 23 were shared between EA and AA. Replication with an additional 10,096 AA individuals identified two previously undescribed FI loci, chrX FAM133A (rs213676) and chr5 PELO (rs6450057). Trans-ethnic analyses with regulatory annotation illuminate the genetic architecture of glycemic traits and suggest gene regulation as a target to advance precision medicine for T2D. Our approach to utilize state-of-the-art functional annotation and implement trans-ethnic association analysis for discovery and fine-mapping offers a framework for further follow-up and characterization of GWAS signals of complex trait loci.

Penetrance of Hemochromatosis in HFE Genotypes Resulting in p.Cys282Tyr and p.[Cys282Tyr];[His63Asp] in the eMERGE Network.

Hereditary hemochromatosis (HH) is a common autosomal-recessive disorder associated with pathogenic HFE variants, most commonly those resulting in p.Cys282Tyr and p.His63Asp. Recommendations on returning incidental findings of HFE variants in individuals undergoing genome-scale sequencing should be informed by penetrance estimates of HH in unselected samples. We used the eMERGE Network, a multicenter cohort with genotype data linked to electronic medical records, to estimate the diagnostic rate and clinical penetrance of HH in 98 individuals homozygous for the variant coding for HFE p.Cys282Tyr and 397 compound heterozygotes with variants resulting in p.[His63Asp];[Cys282Tyr]. The diagnostic rate of HH in males was 24.4% for p.Cys282Tyr homozygotes and 3.5% for compound heterozygotes (p < 0.001); in females, it was 14.0% for p.Cys282Tyr homozygotes and 2.3% for compound heterozygotes (p < 0.001). Only males showed differences across genotypes in transferrin saturation levels (100% of homozygotes versus 37.5% of compound heterozygotes with transferrin saturation > 50%; p = 0.003), serum ferritin levels (77.8% versus 33.3% with serum ferritin > 300 ng/ml; p = 0.006), and diabetes (44.7% versus 28.0%; p = 0.03). No differences were found in the prevalence of heart disease, arthritis, or liver disease, except for the rate of liver biopsy (10.9% versus 1.8% [p = 0.013] in males; 9.1% versus 2% [p = 0.035] in females). Given the higher rate of HH diagnosis than in prior studies, the high penetrance of iron overload, and the frequency of at-risk genotypes, in addition to other suggested actionable adult-onset genetic conditions, opportunistic screening should be considered for p.[Cys282Tyr];[Cys282Tyr] individuals with existing genomic data.

A framework to evaluate the economic impact of pharmacogenomics.

INTRODUCTION: Pharmacogenomics and personalized medicine promise to improve healthcare by increasing drug efficacy and minimizing side effects. There may also be substantial savings realized by eliminating costs associated with failed treatment. This paper describes a framework using health claims data for analyzing the potential value of pharmacogenomic testing in clinical practice. METHODS: We evaluated a model of alternate clinical strategies using asthma patients' data from a retrospective health claims database to determine a potential cost offset. We estimated the likely cost impact of using a hypothetical pharmacogenomic test to determine a preferred initial therapy. We compared the annualized per patient costs distributions under two clinical strategies: testing all patients for a nonresponse genotype prior to treating and testing none. RESULTS: In the Test All strategy, more patients fall into lower cost ranges of the distribution. In our base case (15% phenotype prevalence, 200 US dollars test, 74% overall first-line treatment efficacy and 60% second-line therapy efficacy) the cost savings per patient for a typical run of the testing strategy simulation ranged from 200 US dollars to 767 US dollars (5th and 95th percentile). Genetic variant prevalence, test cost and the cost of choosing the wrong treatment are key parameters in the economic viability of pharmacogenomics in clinical practice. CONCLUSIONS: A general tool for predicting the impact of pharmacogenomic-based diagnostic tests on healthcare costs in asthma patients suggests that upfront testing costs are likely offset by avoided nonresponse costs. We suggest that similar analyses for decision making could be undertaken using claims data in which a population can be stratified by response to a drug.

Trends in the risks and benefits to patients with cancer participating in phase 1 clinical trials.

CONTEXT: In the past, cancer patients entering phase 1 studies confronted the prospects of high risk and unlikely benefit. Over the last decade, cancer drugs under development have become more targeted, and the clinical research environment has become more scrutinized. The impact of these changes on the risks and benefits to patients who participate in phase 1 cancer trials is unknown. OBJECTIVE: To determine trends in the rates of treatment-related (toxic) death, objective response, and serious toxicity and to identify factors associated with these outcomes. DATA SOURCES: We searched abstracts and journal articles reporting the results of phase 1 cancer treatment trials originally submitted to annual meetings of the American Society of Clinical Oncology (ASCO) from 1991 through 2002. STUDY SELECTION: We focused on published single-agent trials that enrolled patients with advanced solid tumors and excluded studies testing agents already approved by the US Food and Drug Administration at the time of the ASCO presentation. DATA EXTRACTION: Multiple observers independently extracted information on trial design, location, sponsorship, types of tumors treated, drug class, route of administration, and clinical outcomes. DATA SYNTHESIS: The overall toxic death rate for 213 studies (involving 6474 cancer patients) published in peer-reviewed journals was 0.54%, while the overall objective response rate was 3.8%. Toxic death rates decreased over the study period, from 1.1% over the first 4 years of the study (1991-1994) to 0.06% over the most recent 4-year period (1999-2002) (P<.01). Response rates also decreased but by proportionally much less. After adjusting for characteristics of the experimental trials and the investigational agents, the odds of a patient dying from an experimental treatment while participating in a trial submitted during the most recent 4-year period were less than one tenth those of a patient participating in a trial submitted during the first 4-year period (odds ratio, 0.09; 95% confidence interval, 0.01-0.67; P = .009). In comparison, the adjusted odds of a patient experiencing an objective response over the same time periods decreased by approximately half (odds ratio, 0.46; 95% confidence interval, 0.32-0.66; P<.001). CONCLUSIONS: The level of risk experienced by cancer patients who participate in phase 1 treatment trials appears to have improved over the 12-year period from 1991 through 2002. Because toxic death rates have decreased more quickly than have objective response rates, the ratio of risk to benefit may have also improved. These changes relate in part to the targeted and less-toxic nature of newer cancer drugs and are coincident with the increased attention that has been paid to the safety of clinical research over the time period we analyzed.

The use of disease-modifying new drugs for multiple sclerosis treatment in private-sector health plans.

OBJECTIVES: The aims of this study were to estimate the effects of demographics, location, severity of multiple sclerosis (MS), comorbidities, plan type, coinsurance levels, and time of entry into the sample on the use of disease-modifying agents. METHODS: A retrospective analysis of medical claims data from 1996 through 2000 was conducted with a sample of MS patients covered by self-insured, employer-sponsored health plans. Proportional hazard analysis with the SAS procedure for proportional hazards regression was used to estimate the impact of the factors of interest on the use of disease-modifying agents. A simulation was conducted to assess the impact of changing drug copayments on the use of disease-modifying agents for MS. RESULTS: The sample included 1807 patients. Patients were followed for as long as possible, but most were observed for <3 years; the mean (SD) follow-up time was 972.88 (440.59) days. Most factors associated with the use of disease-modifying agents were immutable. They included the following: high severity of illness (only marginally related; P = NS); history of seizures (P = 0.03), depression (P < 0.01), or heart disease (P = 0.01); census region of location (P < 0.01); union membership or association with a union member (P < 0.01); drug copayment requirements (P < 0.05); and year of entry into the sample (P < 0.01). In the simulation, a 50% reduction in drug copayments was associated with an increase of the proportion of patients treated with disease-modifying drugs from 41.2% to 54.7%. Patients' and physicians' preferences for treatment could not be measured directly. The true onset of MS may be unknown for many patients, but this would be the case even if medical records or other data were used for this study. CONCLUSIONS: Our analyses showed an association between copayments and the use of disease-modifying drugs for MS. Insurance policies can be tailored to influence the use of disease-modifying drugs, enhancing the quality of care for MS patients and reducing price-related barriers to beneficial treatment. Future research should test whether reducing copayments for MS treatment would reduce the use of other health care services (via better MS treatment that modifies the course of illness), or whether the use of disease-modifying drugs would increase total costs to the plan, resulting in slightly higher premiums.