Validation of claims-based algorithms to identify non-live birth outcomes

PURPOSE

Perinatal epidemiology studies using healthcare utilization databases are often restricted to live births, largely due to the lack of established algorithms to identify non-live births. The study objective was to develop and validate claims-based algorithms for the ascertainment of non-live births.

METHODS

Using the Mass General Brigham Research Patient Data Registry 2000-2014, we assembled a cohort of women enrolled in Medicaid with a non-live birth. Based on ≥1 inpatient or ≥2 outpatient diagnosis/procedure codes, we identified and randomly sampled 100 potential stillbirth, spontaneous abortion, and termination cases each. For the secondary definitions, we excluded cases with codes for other pregnancy outcomes within ±5 days of the outcome of interest and relaxed the definitions for spontaneous abortion and termination by allowing cases with one outpatient diagnosis only. Cases were adjudicated based on medical chart review. We estimated the positive predictive value (PPV) for each outcome.

RESULTS

The PPV was 71.0% (95% CI, 61.1-79.6) for stillbirth; 79.0% (69.7-86.5) for spontaneous abortion, and 93.0% (86.1-97.1) for termination. When excluding cases with adjacent codes for other pregnancy outcomes and further relaxing the definition, the PPV increased to 80.6% (69.5-88.9) for stillbirth, 86.6% (80.5-91.3) for spontaneous abortion and 94.9% (91.1-97.4) for termination. The PPV for the composite outcome using the relaxed definition was 94.4% (92.3-96.1).

CONCLUSIONS

Our findings suggest non-live birth outcomes can be identified in a valid manner in epidemiological studies based on healthcare utilization databases.

Electronic phenotyping of health outcomes of interest using a linked claims-electronic health record database: Findings from a machine learning pilot project

OBJECTIVE

Claims-based algorithms are used in the Food and Drug Administration Sentinel Active Risk Identification and Analysis System to identify occurrences of health outcomes of interest (HOIs) for medical product safety assessment. This project aimed to apply machine learning classification techniques to demonstrate the feasibility of developing a claims-based algorithm to predict an HOI in structured electronic health record (EHR) data.

MATERIALS AND METHODS

We used the 2015-2019 IBM MarketScan Explorys Claims-EMR Data Set, linking administrative claims and EHR data at the patient level. We focused on a single HOI, rhabdomyolysis, defined by EHR laboratory test results. Using claims-based predictors, we applied machine learning techniques to predict the HOI: logistic regression, LASSO (least absolute shrinkage and selection operator), random forests, support vector machines, artificial neural nets, and an ensemble method (Super Learner).

RESULTS

The study cohort included 32 956 patients and 39 499 encounters. Model performance (positive predictive value [PPV], sensitivity, specificity, area under the receiver-operating characteristic curve) varied considerably across techniques. The area under the receiver-operating characteristic curve exceeded 0.80 in most model variations.

DISCUSSION

For the main Food and Drug Administration use case of assessing risk of rhabdomyolysis after drug use, a model with a high PPV is typically preferred. The Super Learner ensemble model without adjustment for class imbalance achieved a PPV of 75.6%, substantially better than a previously used human expert-developed model (PPV = 44.0%).

CONCLUSIONS

It is feasible to use machine learning methods to predict an EHR-derived HOI with claims-based predictors. Modeling strategies can be adapted for intended uses, including surveillance, identification of cases for chart review, and outcomes research.

A General Propensity Score for Signal Identification Using Tree-Based Scan Statistics

The tree-based scan statistic (TreeScan; Martin Kulldorff, Harvard Medical School, Boston, Massachusetts) is a data-mining method that adjusts for multiple testing of correlated hypotheses when screening thousands of potential adverse events for signal identification. Simulation has demonstrated the promise of TreeScan with a propensity score (PS)-matched cohort design. However, it is unclear which variables to include in a PS for applied signal identification studies to simultaneously adjust for confounding across potential outcomes. We selected 4 pairs of medications with well-understood safety profiles. For each pair, we evaluated 5 candidate PSs with different combinations of 1) predefined general covariates (comorbidity, frailty, utilization), 2) empirically selected (data-driven) covariates, and 3) covariates tailored to the drug pair. For each pair, statistical alerting patterns were similar with alternative PSs (≤11 alerts in 7,996 outcomes scanned). Inclusion of covariates tailored to exposure did not appreciably affect screening results. Inclusion of empirically selected covariates can provide better proxy coverage for confounders but can also decrease statistical power. Unlike tailored covariates, empirical and predefined general covariates can be applied "out of the box" for signal identification. The choice of PS depends on the level of concern about residual confounding versus loss of power. Potential signals should be followed by pharmacoepidemiologic assessment where confounding control is tailored to the specific outcome(s) under investigation.

Extension of Disease Risk Score-Based Confounding Adjustments for Multiple Outcomes of Interest: An Empirical Evaluation

Use of disease risk score (DRS)-based confounding adjustment when estimating treatment effects on multiple outcomes is not well studied. We designed an empirical cohort study to compare dabigatran initiators and warfarin initiators with respect to risks of ischemic stroke and major bleeding in 12 sequential monitoring periods (90 days each), using data from the Truven Marketscan database (Truven Health Analytics, Ann Arbor, Michigan). We implemented 2 approaches to combine DRS for multiple outcomes: 1) 1:1 matching on prognostic propensity scores (PPS), created using DRS for bleeding and stroke as independent variables in a propensity score (PS) model; and 2) simultaneous 1:1 matching on DRS for bleeding and stroke using Mahalanobis distance (M-distance), and compared their performance with that of traditional PS matching. M-distance matching appeared to produce more stable results in the early marketing period than both PPS and traditional PS matching; hazard ratios from unadjusted analysis, traditional PS matching, PPS matching, and M-distance matching after 4 periods were 0.72 (95% confidence interval (CI): 0.51, 1.03), 0.61 (95% CI: 0.31, 1.09), 0.55 (95% CI: 0.33, 0.91), and 0.78 (95% CI: 0.45, 1.34), respectively, for stroke and 0.65 (95% CI: 0.53, 0.80), 0.78 (95% CI: 0.60, 1.01), 0.75 (95% CI: 0.59, 0.96), and 0.78 (95% CI: 0.64, 0.95), respectively, for bleeding. In later periods, estimates were similar for traditional PS matching and M-distance matching but suggested potential residual confounding with PPS matching. These results suggest that M-distance matching may be a valid approach for extension of DRS-based confounding adjustments for multiple outcomes of interest.

A Synthesis of Current Surveillance Planning Methods for the Sequential Monitoring of Drug and Vaccine Adverse Effects Using Electronic Health Care Data

INTRODUCTION

The large-scale assembly of electronic health care data combined with the use of sequential monitoring has made proactive postmarket drug- and vaccine-safety surveillance possible. Although sequential designs have been used extensively in randomized trials, less attention has been given to methods for applying them in observational electronic health care database settings.

EXISTING METHODS

We review current sequential-surveillance planning methods from randomized trials, and the Vaccine Safety Datalink (VSD) and Mini-Sentinel Pilot projects-two national observational electronic health care database safety monitoring programs.

FUTURE SURVEILLANCE PLANNING

Based on this examination, we suggest three steps for future surveillance planning in health care databases: (1) prespecify the sequential design and analysis plan, using available feasibility data to reduce assumptions and minimize later changes to initial plans; (2) assess existing drug or vaccine uptake, to determine if there is adequate information to proceed with surveillance, before conducting more resource-intensive planning; and (3) statistically evaluate and clearly communicate the sequential design with all those designing and interpreting the safety-surveillance results prior to implementation. Plans should also be flexible enough to accommodate dynamic and often unpredictable changes to the database information made by the health plans for administrative purposes.

CONCLUSIONS

This paper is intended to encourage dialogue about establishing a more systematic, scalable, and transparent sequential design-planning process for medical-product safety-surveillance systems utilizing observational electronic health care databases. Creating such a framework could yield improvements over existing practices, such as designs with increased power to assess serious adverse events.

Challenges in evaluating cancer as a clinical outcome in postapproval studies of drug safety

Pharmaceuticals approved in the United States are largely not known human carcinogens. However, cancer signals associated with pharmaceuticals may be hypothesized or arise after product approval. There are many study designs that can be used to evaluate cancer as an outcome in the postapproval setting. Because prospective systematic collection of cancer outcomes from a large number of individuals may be lengthy, expensive, and challenging, leveraging data from large existing databases are an integral approach. Such studies have the capability to evaluate the clinical experience of a large number of individuals, yet there are unique methodological challenges involved in their use to evaluate cancer outcomes. To discuss methodological challenges and potential solutions, the Food and Drug Administration and the National Cancer Institute convened a two-day public meeting in 2014. This commentary summarizes the most salient issues discussed at the meeting.

Initiation of tumor necrosis factor α antagonists and risk of fractures in patients with selected rheumatic and autoimmune diseases

OBJECTIVE

We tested the hypothesis that initiation of tumor necrosis factor α (TNFα) antagonists reduced the risk of fractures compared to nonbiologic comparators in patients with autoimmune diseases.

METHODS

Using 4 large administrative databases, we assembled retrospective cohorts of patients with autoimmune diseases who initiated either a TNFα antagonist or a nonbiologic medication. We identified 3 mutually exclusive disease groups: rheumatoid arthritis (RA), inflammatory bowel disease (IBD), and a combined group: psoriasis (PsO), psoriatic arthritis (PsA), or ankylosing spondylitis (AS). We used baseline covariate data to calculate propensity scores (PS) for each disease group and used Cox regression to calculate hazard ratios (HRs) and 95% confidence intervals (95% CIs). We compared the risk of combined hip, radius/ulna, humerus, or pelvic fractures between PS-matched cohorts of new users of TNFα antagonists and nonbiologic comparators.

RESULTS

We identified 9,020, 2,014, and 2,663 new PS-matched episodes of TNFα antagonist and nonbiologic comparator use in RA, IBD, and PsO-PsA-AS cohorts, respectively. The risk of combined fractures was similar between new users of TNFα antagonists and nonbiologic comparators for each disease (HR 1.17, 95% CI 0.91-1.51; HR 1.49, 95% CI 0.72-3.11; and HR 0.92, 95% CI 0.47-1.82 for RA, IBD, and PsO-PsA-AS, respectively). In RA, the risk of combined fractures was associated with an average daily dosage of prednisone equivalents >10 mg/day at baseline compared with no glucocorticoid (HR 1.54, 95% CI 1.03-2.30).

CONCLUSION

The risk of fractures did not differ between initiators of a biologic agent and a nonbiologic comparator for any disease studied. Among RA patients, use of >10 mg/day of prednisone equivalents at baseline increased the fracture risk.

Rates of hospitalized bacterial infection associated with juvenile idiopathic arthritis and its treatment

OBJECTIVE

To compare the incidence of hospitalized bacterial infections among children with and children without juvenile idiopathic arthritis (JIA) and to examine the effects of selected medications.

METHODS

Using national Medicaid data from 2000 through 2005, we identified a cohort of children with JIA and a comparator cohort of children with attention deficit hyperactivity disorder (ADHD). Exposures to methotrexate (MTX), TNF inhibitors, and oral glucocorticoids (GCs) were determined using pharmacy claims. Patients hospitalized with bacterial infections were identified using coded discharge diagnoses. We calculated adjusted hazard ratios (HR(adj) ) to compare infection incidence rates while adjusting for relevant covariates.

RESULTS

We identified 8,479 JIA patients with 13,003 person-years of followup; 36% took MTX and 16% took TNF inhibitors. Compared with ADHD patients, JIA patients who were not currently taking MTX or TNF inhibitors had an increased rate of infection (HR(adj) 2.0 [95% confidence interval (95% CI) 1.5, 2.5]). Among JIA patients not receiving TNF inhibitor therapy, MTX users had a similar rate of infection as those not currently taking MTX (HR(adj) 1.2 [95% CI 0.9, 1.7]). TNF inhibitor use (irrespective of MTX) resulted in a similar rate of infection as use of MTX without a TNF inhibitor (HR(adj) 1.2 [95% CI 0.8, 1.8]). Use of high-dose GCs (≥10 mg/day of prednisone or equivalent) increased the rate of infection as compared with no GC use, after adjustment for MTX and TNF inhibitor use (HR(adj) 3.1 [95% CI 2.0, 4.7]).

CONCLUSION

Children with JIA had an increased rate of infection compared to children with ADHD. Among children with JIA, the rate of infection was not increased with MTX or TNF inhibitor use, but was significantly increased with high-dose GC use.

Recent combined hormonal contraceptives (CHCs) and the risk of thromboembolism and other cardiovascular events in new users

BACKGROUND

Combined hormonal contraceptives (CHCs) place women at increased risk of venous thromboembolic events (VTEs) and arterial thrombotic events (ATEs), including acute myocardial infarction and ischemic stroke. There is concern that three recent CHC preparations [drospirenone-containing pills (DRSPs), the norelgestromin-containing transdermal patch (NGMN) and the etonogestrel vaginal ring (ETON)] may place women at even higher risk of thrombosis than other older low-dose CHCs with a known safety profile.

STUDY DESIGN

All VTEs and all hospitalized ATEs were identified in women, ages 10-55 years, from two integrated health care programs and two state Medicaid programs during the time period covering their new use of DRSP, NGMN, ETON or one of four low-dose estrogen comparator CHCs. The relative risk of thrombotic and thromboembolic outcomes associated with the newer CHCs in relation to the comparators was assessed with Cox proportional hazards regression models adjusting for age, site and year of entry into the study.

RESULTS

The hazards ratio for DRSP in relation to low-dose estrogen comparators among new users was 1.77 (95% confidence interval 1.33-2.35) for VTE and 2.01 (1.06-3.81) for ATE. The increased risk of DRSP was limited to the 10-34-year age group for VTE and the 35-55-year group for ATE. Use of the NGMN patch and ETON vaginal ring was not associated with increased risk of either thromboembolic or thrombotic outcomes.

CONCLUSIONS

In new users, DRSP was associated with higher risk of thrombotic events (VTE and ATE) relative to low-dose estrogen comparator CHCs, while the use of the NGMN patch and ETON vaginal ring was not.

Initiation of tumor necrosis factor-α antagonists and the risk of hospitalization for infection in patients with autoimmune diseases

CONTEXT

Although tumor necrosis factor (TNF)-α antagonists are increasingly used in place of nonbiologic comparator medications, their safety profile remains incomplete.

OBJECTIVES

To determine whether initiation of TNF-α antagonists compared with nonbiologic comparators is associated with an increased risk of serious infections requiring hospitalization.

DESIGN, SETTING, AND PATIENTS

Within a US multi-institutional collaboration, we assembled retrospective cohorts (1998-2007) of patients with rheumatoid arthritis (RA), inflammatory bowel disease (IBD), and psoriasis, psoriatic arthritis, or ankylosing spondylitis (psoriasis and spondyloarthropathies) combining data from Kaiser Permanente Northern California, New Jersey and Pennsylvania Pharmaceutical Assistance programs, Tennessee Medicaid, and national Medicaid/Medicare. TNF-α antagonists and nonbiologic regimens were compared in disease-specific propensity score (PS)-matched cohorts using Cox regression models with nonbiologics as the reference. Baseline glucocorticoid use was evaluated as a separate covariate.

MAIN OUTCOME MEASURE

Infections requiring hospitalization (serious infections) during the first 12 months after initiation of TNF-α antagonists or nonbiologic regimens.

RESULTS

Study cohorts included 10,484 RA, 2323 IBD, and 3215 psoriasis and spondyloarthropathies matched pairs using TNF-α antagonists and comparator medications. Overall, we identified 1172 serious infections, most of which (53%) were pneumonia and skin and soft tissue infections. Among patients with RA, serious infection hospitalization rates were 8.16 (TNF-α antagonists) and 7.78 (comparator regimens) per 100 person-years (adjusted hazard ratio [aHR], 1.05 [95% CI, 0.91-1.21]). Among patients with IBD, rates were 10.91 (TNF-α antagonists) and 9.60 (comparator) per 100 person-years (aHR, 1.10 [95% CI, 0.83-1.46]). Among patients with psoriasis and spondyloarthropathies, rates were 5.41 (TNF-α antagonists) and 5.37 (comparator) per 100 person-years (aHR, 1.05 [95% CI, 0.76-1.45]). Among patients with RA, infliximab was associated with a significant increase in serious infections compared with etanercept (aHR, 1.26 [95% CI, 1.07-1.47]) and adalimumab (aHR, 1.23 [95% CI, 1.02-1.48]). Baseline glucocorticoid use was associated with a dose-dependent increase in infections.

CONCLUSION

Among patients with autoimmune diseases, compared with treatment with nonbiologic regimens, initiation of TNF-α antagonists was not associated with an increased risk of hospitalizations for serious infections.

Risk of acute myocardial infarction, stroke, heart failure, and death in elderly Medicare patients treated with rosiglitazone or pioglitazone

CONTEXT

Studies have suggested that the use of rosiglitazone may be associated with an increased risk of serious cardiovascular events compared with other treatments for type 2 diabetes.

OBJECTIVE

To determine if the risk of serious cardiovascular harm is increased by rosiglitazone compared with pioglitazone, the other thiazolidinedione marketed in the United States.

DESIGN, SETTING, AND PATIENTS

Nationwide, observational, retrospective, inception cohort of 227,571 Medicare beneficiaries aged 65 years or older (mean age, 74.4 years) who initiated treatment with rosiglitazone or pioglitazone through a Medicare Part D prescription drug plan from July 2006-June 2009 and who underwent follow-up for up to 3 years after thiazolidinedione initiation.

MAIN OUTCOME MEASURES

Individual end points of acute myocardial infarction (AMI), stroke, heart failure, and all-cause mortality (death), and composite end point of AMI, stroke, heart failure, or death, assessed using incidence rates by thiazolidinedione, attributable risk, number needed to harm, Kaplan-Meier plots of time to event, and Cox proportional hazard ratios for time to event, adjusted for potential confounding factors, with pioglitazone as reference.

RESULTS

A total of 8667 end points were observed during the study period. The adjusted hazard ratio for rosiglitazone compared with pioglitazone was 1.06 (95% confidence interval [CI], 0.96-1.18) for AMI; 1.27 (95% CI, 1.12-1.45) for stroke; 1.25 (95% CI, 1.16-1.34) for heart failure; 1.14 (95% CI, 1.05-1.24) for death; and 1.18 (95% CI, 1.12-1.23) for the composite of AMI, stroke, heart failure, or death. The attributable risk for this composite end point was 1.68 (95% CI, 1.27-2.08) excess events per 100 person-years of treatment with rosiglitazone compared with pioglitazone. The corresponding number needed to harm was 60 (95% CI, 48-79) treated for 1 year.

CONCLUSION

Compared with prescription of pioglitazone, prescription of rosiglitazone was associated with an increased risk of stroke, heart failure, and all-cause mortality and an increased risk of the composite of AMI, stroke, heart failure, or all-cause mortality in patients 65 years or older.

Perspectives on the use of data mining in pharmaco-vigilance

In the last 5 years, regulatory agencies and drug monitoring centres have been developing computerised data-mining methods to better identify reporting relationships in spontaneous reporting databases that could signal possible adverse drug reactions. At present, there are no guidelines or standards for the use of these methods in routine pharmaco-vigilance. In 2003, a group of statisticians, pharmaco-epidemiologists and pharmaco-vigilance professionals from the pharmaceutical industry and the US FDA formed the Pharmaceutical Research and Manufacturers of America-FDA Collaborative Working Group on Safety Evaluation Tools to review best practices for the use of these methods.In this paper, we provide an overview of: (i) the statistical and operational attributes of several currently used methods and their strengths and limitations; (ii) information about the characteristics of various postmarketing safety databases with which these tools can be deployed; (iii) analytical considerations for using safety data-mining methods and interpreting the results; and (iv) points to consider in integration of safety data mining with traditional pharmaco-vigilance methods. Perspectives from both the FDA and the industry are provided. Data mining is a potentially useful adjunct to traditional pharmaco-vigilance methods. The results of data mining should be viewed as hypothesis generating and should be evaluated in the context of other relevant data. The availability of a publicly accessible global safety database, which is updated on a frequent basis, would further enhance detection and communication about safety issues.

Drinking water arsenic in Utah: A cohort mortality study

The association of drinking water arsenic and mortality outcome was investigated in a cohort of residents from Millard County, Utah. Median drinking water arsenic concentrations for selected study towns ranged from 14 to 166 ppb and were from public and private samples collected and analyzed under the auspices of the State of Utah Department of Environmental Quality, Division of Drinking Water. Cohort members were assembled using historical documents of the Church of Jesus Christ of Latter-day Saints. Standard mortality ratios (SMRs) were calculated. Using residence history and median drinking water arsenic concentration, a matrix for cumulative arsenic exposure was created. Without regard to specific exposure levels, statistically significant findings include increased mortality from hypertensive heart disease [SMR = 2.20; 95% confidence interval (CI), 1.36-3.36], nephritis and nephrosis (SMR = 1.72; CI, 1.13-2.50), and prostate cancer (SMR = 1.45; CI, 1.07-1. 91) among cohort males. Among cohort females, statistically significant increased mortality was found for hypertensive heart disease (SMR = 1.73; CI, 1.11-2.58) and for the category of all other heart disease, which includes pulmonary heart disease, pericarditis, and other diseases of the pericardium (SMR = 1.43; CI, 1.11-1.80). SMR analysis by low, medium, and high arsenic exposure groups hinted at a dose relationship for prostate cancer. Although the SMRs by exposure category were elevated for hypertensive heart disease for both males and females, the increases were not sequential from low to high groups. Because the relationship between health effects and exposure to drinking water arsenic is not well established in U.S. populations, further evaluation of effects in low-exposure populations is warranted.

Bladder cancer incidence in arylamine workers

Cancer incidence was investigated in a cohort of 700 workers employed at a Connecticut chemical plant between mid-1965 and 1989. The plant produced a variety of chemicals, including arylamines such as dichlorobenzidine (DCB), o-dianisidine, o-tolidine, but not benzidine. Benzidine production ceased prior to mid-1965. The principal finding was a statistically significant increase in the standardized incidence ratio (SIR) for bladder cancer in men (SIR = 8.3; confidence interval, 3.3 to 17.0). Based on an exposure classification system developed by a panel of former and current employees, the observed association between bladder cancer cases and exposure to arylamines increased with increasing exposure (SIRs = 0.0, 5.5, 16.4, for none, low, or moderate levels of exposure, respectively). Smoking probably contributed to the bladder cancer risk, as all case subjects were known to be current or former cigarette smokers.

Miscarriages among female physical therapists who report using radio- and microwave-frequency electromagnetic radiation

Physical therapists are exposed to radio- and microwave-frequency electromagnetic radiation by operating shortwave and microwave diathermy units. Recent studies suggest that use of shortwave diathermy is associated with an excess risk of birth defects, perinatal deaths, and late spontaneous abortions among the offspring of exposed female therapists. To assess the impact of occupational use of microwave and shortwave diathermy at the time of conception, the authors mailed questionnaires to 42,403 physical therapists in 1989. Both occupational and reproductive histories were obtained. Exposures to shortwave and microwave diathermy were both assessed in the same fashion and were examined in relation to early recognized fetal loss in a nested case-control design. A total of 1,753 case pregnancies (miscarriages) were matched to 1,753 incidence density control pregnancies (other pregnancies except ectopic pregnancies). A pregnancy was considered "exposed" if the mother reported using microwave or shortwave diathermy anytime during the 6 months prior to the first trimester or during the first trimester. Pregnancies of mothers reporting microwave use 6 months prior to the pregnancy or during the first trimester were more likely to result in miscarriage (odds ratio (OR) = 1.28, 95% confidence interval (CI) 1.02-1.59). The odds ratio increased with increasing level of exposure (chi 2 = 7.25, p < 0.005). The odds ratio in the highest exposure group (20 or more exposures/month) was 1.59. The overall odds ratio was slightly lower after it was controlled for prior fetal loss (OR = 1.26, 95% CI 1.00-1.59), but the exposure-response effect remained (chi 2 = 5.17, p < 0.01). The risk of miscarriage was not associated with reported use of shortwave diathermy equipment (OR = 1.07, 95% CI 0.91-1.24). The odds ratio in the highest exposure group was 0.87.

A multivariate analysis of risk factors for hepatitis B virus infection among hospital employees screened for vaccination

Previous studies of risk factors for hepatitis B virus infection among hospital employees have been based on surveys in single institutions or have been analyzed with univariate techniques. From November 1980 through August 1981, the authors performed a multi-institutional seroepidemiologic survey of hospital employees screened for entrance into a hepatitis B vaccine trial who represented groups at high risk for hepatitis B infection. Using a logistic regression model for the analysis of risk factors, the investigators determined the relative odds and 95% confidence intervals for risk of hepatitis B infection to be as follows: race (nonwhite/white: 3.4; 2.4-4.8) (p less than 0.001); history of acute viral hepatitis of an unspecified type (3.6; 2.2-5.9) (p less than 0.001); and employment at hospitals 1 through 5 as compared with hospital 6 (1.8; 1.1-2.9) (p = 0.015). In addition, certain job categories and the duration of employment within some of these categories were associated with increasing risk for hepatitis B infection over time. Laboratory workers (1.4; 1.2-1.7), surgical staff (1.2; 1.1-1.4), and medical staff (1.3; 1.1-1.5) had significant (p less than 0.05) increased risk of prior infection with longer duration of employment. Such time-job interaction was not demonstrable for nursing staff, anesthesiology staff, dental personnel, pathology staff, or ancillary personnel. The logistic regression model also shows that the highest gradient of risk for laboratory workers, surgeons, and medical staff occurs during the first five years of employment. An effective preventive strategy, such as the use of hepatitis B vaccine, should be targeted for these groups at the time of initial employment.

Hepatitis B vaccine in health care personnel: safety, immunogenicity, and indicators of efficacy

In a double-blind trial, we randomly assigned 1330 high-risk health care personnel to receive three 20-micrograms doses of hepatitis B vaccine or placebo. Among vaccine recipients 58% responded within 1 month and 97% within 9 months; there was no difference in immune response to the vaccine between men and women. Efficacy was evaluated after a mean follow-up of only 13.2 months, just before the vaccine was released commercially. Five hepatitis B infections were identified in placebo recipients and one in a vaccine recipient. Although the number of infections was too small to allow confident conclusions about protective efficacy of the vaccine, we saw a 67% reduction in the need for hepatitis B immune globulin after accidental hepatitis B inoculation in the vaccine group (relative risk, 5.08; 95% confidence intervals, 1.3 to 19.9). Minor side effects occurred with equal frequency after vaccine (28.7%) and placebo (27.2%) injections; no participant had a severe adverse reaction. Vaccination with the 20-micrograms hepatitis B vaccine was highly immunogenic and safe in health care workers.