Pooled individual patient data from five countries were used to derive a clinical prediction rule for coronary artery disease in primary care.

OBJECTIVE: To construct a clinical prediction rule for coronary artery disease (CAD) presenting with chest pain in primary care. STUDY DESIGN AND SETTING: Meta-Analysis using 3,099 patients from five studies. To identify candidate predictors, we used random forest trees, multiple imputation of missing values, and logistic regression within individual studies. To generate a prediction rule on the pooled data, we applied a regression model that took account of the differing standard data sets collected by the five studies. RESULTS: The most parsimonious rule included six equally weighted predictors: age ≥55 (males) or ≥65 (females) (+1); attending physician suspected a serious diagnosis (+1); history of CAD (+1); pain brought on by exertion (+1); pain feels like "pressure" (+1); pain reproducible by palpation (-1). CAD was considered absent if the prediction score is <2. The area under the ROC curve was 0.84. We applied this rule to a study setting with a CAD prevalence of 13.2% using a prediction score cutoff of <2 (i.e., -1, 0, or +1). When the score was <2, the probability of CAD was 2.1% (95% CI: 1.1-3.9%); when the score was ≥ 2, it was 43.0% (95% CI: 35.8-50.4%). CONCLUSIONS: Clinical prediction rules are a key strategy for individualizing care. Large data sets based on electronic health records from diverse sites create opportunities for improving their internal and external validity. Our patient-level meta-analysis from five primary care sites should improve external validity. Our strategy for addressing site-to-site systematic variation in missing data should improve internal validity. Using principles derived from decision theory, we also discuss the problem of setting the cutoff prediction score for taking action.

Coronary heart disease in primary care: accuracy of medical history and physical findings in patients with chest pain--a study protocol for a systematic review with individual patient data.

BACKGROUND: Chest pain is a common complaint in primary care, with coronary heart disease (CHD) being the most concerning of many potential causes. Systematic reviews on the sensitivity and specificity of symptoms and signs summarize the evidence about which of them are most useful in making a diagnosis. Previous meta-analyses are dominated by studies of patients referred to specialists. Moreover, as the analysis is typically based on study-level data, the statistical analyses in these reviews are limited while meta-analyses based on individual patient data can provide additional information. Our patient-level meta-analysis has three unique aims. First, we strive to determine the diagnostic accuracy of symptoms and signs for myocardial ischemia in primary care. Second, we investigate associations between study- or patient-level characteristics and measures of diagnostic accuracy. Third, we aim to validate existing clinical prediction rules for diagnosing myocardial ischemia in primary care. This article describes the methods of our study and six prospective studies of primary care patients with chest pain. Later articles will describe the main results. METHODS/DESIGN: We will conduct a systematic review and IPD meta-analysis of studies evaluating the diagnostic accuracy of symptoms and signs for diagnosing coronary heart disease in primary care. We will perform bivariate analyses to determine the sensitivity, specificity and likelihood ratios of individual symptoms and signs and multivariate analyses to explore the diagnostic value of an optimal combination of all symptoms and signs based on all data of all studies. We will validate existing clinical prediction rules from each of the included studies by calculating measures of diagnostic accuracy separately by study. DISCUSSION: Our study will face several methodological challenges. First, the number of studies will be limited. Second, the investigators of original studies defined some outcomes and predictors differently. Third, the studies did not collect the same standard clinical data set. Fourth, missing data, varying from partly missing to fully missing, will have to be dealt with.Despite these limitations, we aim to summarize the available evidence regarding the diagnostic accuracy of symptoms and signs for diagnosing CHD in patients presenting with chest pain in primary care. REVIEW REGISTRATION: Centre for Reviews and Dissemination (University of York): CRD42011001170.

Telephone care management to improve cancer screening among low-income women: a randomized, controlled trial.

BACKGROUND: Minority and low-income women receive fewer cancer screenings than other women. OBJECTIVE: To evaluate the effect of a telephone support intervention to increase rates of breast, cervical, and colorectal cancer screening among minority and low-income women. DESIGN: Randomized, controlled trial conducted between November 2001 and April 2004. SETTING: 11 community and migrant health centers in New York City. PATIENTS: 1413 women who were overdue for cancer screening. INTERVENTION: Over 18 months, women assigned to the intervention group received an average of 4 calls from prevention care managers and women assigned to the control group received usual care. Follow-up data were available for 99% of women, and 91% of the intervention group received at least 1 call. MEASUREMENTS: Medical record documentation of mammography, Papanicolaou testing, and colorectal cancer screening according to U.S. Preventive Services Task Force recommendations. RESULTS: The proportion of women who had mammography increased from 0.58 to 0.68 with the intervention and decreased from 0.60 to 0.58 with usual care; the proportion who had Papanicolaou testing increased from 0.71 to 0.78 with the intervention and was unchanged with usual care; and the proportion who had colorectal screening increased from 0.39 to 0.63 with the intervention and from 0.39 to 0.50 with usual care. The difference in the change in screening rates between groups was 0.12 for mammography (95% CI, 0.06 to 0.19), 0.07 for Papanicolaou testing (CI, 0.01 to 0.12), and 0.13 for colorectal screening (CI, 0.07 to 0.19). The proportion of women who were up to date for 3 tests increased from 0.21 to 0.43 with the intervention. LIMITATIONS: Participants were from 1 city and had access to a regular source of care. Medical records may not have captured all cancer screenings. CONCLUSIONS: Telephone support can improve cancer screening rates among women who visit community and migrant health centers. The intervention seems to be well suited to health plans, large medical groups, and other organizations that seek to increase cancer screening rates and to address disparities in care.

Perceptions of barriers and facilitators of cancer early detection among low-income minority women in community health centers.

African-American and Hispanic women receive fewer indicated cancer early detection services than do majority women. Low rates of cancer screening may, in part, explain the disproportionately higher rates of cancer deaths in this population. The aim of this qualitative study was to explore through individual interviews the perceptions of barriers and facilitators of colorectal, cervical and breast cancer screening among 187 low-income, primarily minority women in four New-York-City-based community/migrant health centers. We identified various barriers and facilitators within each of these categories. Clinician recommendation was the most commonly cited encouragement to cancer screening. Other facilitators of cancer screening identified by patients included personal medical history, such as the presence of a symptom. The perception of screening as routine was cited as a facilitator far more commonly for mammography and Pap tests than for either of the colorectal screenings. Less commonly cited facilitators were insurance coverage and information from the media. The most common barriers were a lack of cancer screening knowledge, patients' perception of good health or absence of symptoms attributable to ill health, fear of pain from the cancer test and a lack of a clinician recommendation. Using standard qualitative techniques, patients' responses were analyzed and grouped into a taxonomy of three major categories reflecting: (1) patients' attitudes and beliefs, (2) their social network experience and (3) accessibility of services. This taxonomy may serve as a useful framework for primary care providers to educate and counsel their patients about cancer screening behaviors.