Comparison of imputation methods for handling missing covariate data when fitting a Cox proportional hazards model: a resampling study

<p>Abstract</p> <p>Background</p> <p>The appropriate handling of missing covariate data in prognostic modelling studies is yet to be conclusively determined. A resampling study was performed to investigate the effects of different missing data methods on the performance of a prognostic model.</p> <p>Methods</p> <p>Observed data for 1000 cases were sampled with replacement from a large complete dataset of 7507 patients to obtain 500 replications. Five levels of missingness (ranging from 5% to 75%) were imposed on three covariates using a missing at random (MAR) mechanism. Five missing data methods were applied; a) complete case analysis (CC) b) single imputation using regression switching with predictive mean matching (SI), c) multiple imputation using regression switching imputation, d) multiple imputation using regression switching with predictive mean matching (MICE-PMM) and e) multiple imputation using flexible additive imputation models. A Cox proportional hazards model was fitted to each dataset and estimates for the regression coefficients and model performance measures obtained.</p> <p>Results</p> <p>CC produced biased regression coefficient estimates and inflated standard errors (SEs) with 25% or more missingness. The underestimated SE after SI resulted in poor coverage with 25% or more missingness. Of the MI approaches investigated, MI using MICE-PMM produced the least biased estimates and better model performance measures. However, this MI approach still produced biased regression coefficient estimates with 75% missingness.</p> <p>Conclusions</p> <p>Very few differences were seen between the results from all missing data approaches with 5% missingness. However, performing MI using MICE-PMM may be the preferred missing data approach for handling between 10% and 50% MAR missingness.</p

Distribution of Major Health Risks: Findings from the Global Burden of Disease Study

BACKGROUND: Most analyses of risks to health focus on the total burden of their aggregate effects. The distribution of risk-factor-attributable disease burden, for example by age or exposure level, can inform the selection and targeting of specific interventions and programs, and increase cost-effectiveness. METHODS AND FINDINGS: For 26 selected risk factors, expert working groups conducted comprehensive reviews of data on risk-factor exposure and hazard for 14 epidemiological subregions of the world, by age and sex. Age-sex-subregion-population attributable fractions were estimated and applied to the mortality and burden of disease estimates from the World Health Organization Global Burden of Disease database. Where possible, exposure levels were assessed as continuous measures, or as multiple categories. The proportion of risk-factor-attributable burden in different population subgroups, defined by age, sex, and exposure level, was estimated. For major cardiovascular risk factors (blood pressure, cholesterol, tobacco use, fruit and vegetable intake, body mass index, and physical inactivity) 43%–61% of attributable disease burden occurred between the ages of 15 and 59 y, and 87% of alcohol-attributable burden occurred in this age group. Most of the disease burden for continuous risks occurred in those with only moderately raised levels, not among those with levels above commonly used cut-points, such as those with hypertension or obesity. Of all disease burden attributable to being underweight during childhood, 55% occurred among children 1–3 standard deviations below the reference population median, and the remainder occurred among severely malnourished children, who were three or more standard deviations below median. CONCLUSIONS: Many major global risks are widely spread in a population, rather than restricted to a minority. Population-based strategies that seek to shift the whole distribution of risk factors often have the potential to produce substantial reductions in disease burden

Usual Primary Care Provider Characteristics of a Patient-Centered Medical Home and Mental Health Service Use

BACKGROUND: The benefits of the patient-centered medical home (PCMH) over and above that of a usual source of medical care have yet to be determined, particularly for adults with mental health disorders. OBJECTIVE: To examine qualities of a usual provider that align with PCMH goals of access, comprehensiveness, and patient-centered care, and to determine whether PCMH qualities in a usual provider are associated with the use of mental health services (MHS). DESIGN: Using national data from the Medical Expenditure Panel Survey, we conducted a lagged cross-sectional study of MHS use subsequent to participant reports of psychological distress and usual provider and practice characteristics. PARTICIPANTS: A total of 2,358 adults, aged 18–64 years, met the criteria for serious psychological distress and reported on their usual provider and practice characteristics. MAIN MEASURES: We defined “usual provider” as a primary care provider/practice, and “PCMH provider” as a usual provider that delivered accessible, comprehensive, patient-centered care as determined by patient self-reporting. The dependent variable, MHS, included self-reported mental health visits to a primary care provider or mental health specialist, counseling, and psychiatric medication treatment over a period of 1 year. RESULTS: Participants with a usual provider were significantly more likely than those with no usual provider to have experienced a primary care mental health visit (marginal effect [ME] = 8.5, 95 % CI = 3.2–13.8) and to have received psychiatric medication (ME = 15.5, 95 % CI = 9.4–21.5). Participants with a PCMH were additionally more likely than those with no usual provider to visit a mental health specialist (ME = 7.6, 95 % CI = 0.7–14.4) and receive mental health counseling (ME = 8.5, 95 % CI = 1.5–15.6). Among those who reported having had any type of mental health visit, participants with a PCMH were more likely to have received mental health counseling than those with only a usual provider (ME = 10.0, 95 % CI = 1.0–19.0). CONCLUSIONS: Access to a usual provider is associated with increased receipt of needed MHS. Patients who have a usual provider with PCMH qualities are more likely to receive mental health counseling