Biomedical subjects

P J Heagerty

Publications and source records attributed to P J Heagerty.

7 recordsLinked to original sources

PubMed2002

MR nerve imaging in a prospective cohort of patients with suspected carpal tunnel syndrome.

OBJECTIVES: To evaluate the reliability and diagnostic accuracy of high-resolution MRI of the median nerve in a prospectively assembled cohort of subjects with clinically suspected carpal tunnel syndrome (CTS). METHODS: The authors prospectively identified 120 subjects with clinically suspected CTS from five Seattle-area clinics. All subjects completed a hand-pain diagram and underwent a standardized nerve conduction study (NCS). The reference standard for determining CTS status was a classic or probable hand pain diagram and NCS with a difference >0.3 ms between the 8-cm median and ulnar peak latencies. Readers graded multiple imaging parameters of the MRI on four-point scales. The authors also performed quantitative measurements of both the median nerve and carpal tunnel cross-sectional areas. NCS and MRI were interpreted without knowledge of the other study or the hand pain diagram. RESULTS: Intrareader reliability was substantial to near perfect (kappa = 0.76 to 0.88). Interreader agreement was lower but still substantial (kappa = 0.60 to 0.67). Sensitivity of MRI was greatest for the overall impression of the images (96%) followed by increased median nerve signal (91%); however, specificities were low (33 to 38%). The length of abnormal signal on T2-weighted images was significantly correlated with nerve conduction latency, and median nerve area was larger at the distal radioulnar joint (15.8 vs 11.8 mm(2)) in patients with CTS. A logistic regression model combining these two MR variables had a receiver operating characteristic area under the curve of 0.85. CONCLUSIONS: The reliability of MRI is high but the diagnostic accuracy is only moderate compared with a research-definition reference standard.

Adult↗

PubMed2000

Time-dependent ROC curves for censored survival data and a diagnostic marker.

ROC curves are a popular method for displaying sensitivity and specificity of a continuous diagnostic marker, X, for a binary disease variable, D. However, many disease outcomes are time dependent, D(t), and ROC curves that vary as a function of time may be more appropriate. A common example of a time-dependent variable is vital status, where D(t) = 1 if a patient has died prior to time t and zero otherwise. We propose summarizing the discrimination potential of a marker X, measured at baseline (t = 0), by calculating ROC curves for cumulative disease or death incidence by time t, which we denote as ROC(t). A typical complexity with survival data is that observations may be censored. Two ROC curve estimators are proposed that can accommodate censored data. A simple estimator is based on using the Kaplan-Meier estimator for each possible subset X > c. However, this estimator does not guarantee the necessary condition that sensitivity and specificity are monotone in X. An alternative estimator that does guarantee monotonicity is based on a nearest neighbor estimator for the bivariate distribution function of (X, T), where T represents survival time (Akritas, M. J., 1994, Annals of Statistics 22, 1299-1327). We present an example where ROC(t) is used to compare a standard and a modified flow cytometry measurement for predicting survival after detection of breast cancer and an example where the ROC(t) curve displays the impact of modifying eligibility criteria for sample size and power in HIV prevention trials.

Breast Neoplasms↗

PubMed2000

Multivariate continuation ratio models: connections and caveats.

We develop semiparametric estimation methods for a pair of regressions that characterize the first and second moments of clustered discrete survival times. In the first regression, we represent discrete survival times through univariate continuation indicators whose expectations are modeled using a generalized linear model. In the second regression, we model the marginal pairwise association of survival times using the Clayton-Oakes cross-product ratio (Clayton, 1978, Biometrika 65, 141-151; Oakes, 1989, Journal of the American Statistical Association 84, 487-493). These models have recently been proposed by Shih (1998, Biometrics 54, 1115-1128). We relate the discrete survival models to multivariate multinomial models presented in Heagerty and Zeger (1996, Journal of the American Statistical Society 91, 1024-1036) and derive a paired estimating equations procedure that is computationally feasible for moderate and large clusters. We extend the work of Guo and Lin (1994, Biometrics 50, 632-639) and Shih (1998) to allow covariance weighted estimating equations and investigate the impact of weighting in terms of asymptotic relative efficiency. We demonstrate that the multinomial structure must be acknowledged when adopting weighted estimating equations and show that a naive use of GEE methods can lead to inconsistent parameter estimates. Finally, we illustrate the proposed methodology by analyzing psychological testing data previously summarized by TenHave and Uttal (1994, Applied Statistics 43, 371-384) and Guo and Lin (1994).

Analysis of Variance↗

PubMed1999

Marginally specified logistic-normal models for longitudinal binary data.

Likelihood-based inference for longitudinal binary data can be obtained using a generalized linear mixed model (Breslow, N. and Clayton, D. G., 1993, Journal of the American Statistical Association 88, 9-25; Wolfinger, R. and O'Connell, M., 1993, Journal of Statistical Computation and Simulation 48, 233-243), given the recent improvements in computational approaches. Alternatively, Fitzmaurice and Laird (1993, Biometrika 80, 141-151), Molenberghs and Lesaffre (1994, Journal of the American Statistical Association 89, 633-644), and Heagerty and Zeger (1996, Journal of the American Statistical Association 91, 1024-1036) have developed a likelihood-based inference that adopts a marginal mean regression parameter and completes full specification of the joint multivariate distribution through either canonical and/or marginal higher moment assumptions. Each of these marginal approaches is computationally intense and currently limited to small cluster sizes. In this manuscript, an alternative parameterization of the logistic-normal random effects model is adopted, and both likelihood and estimating equation approaches to parameter estimation are studied. A key feature of the proposed approach is that marginal regression parameters are adopted that still permit individual-level predictions or contrasts. An example is presented where scientific interest is in both the mean response and the covariance among repeated measurements.

Biometry↗

PubMed1997

Expression of cell-cycle regulators p27Kip1 and cyclin E, alone and in combination, correlate with survival in young breast cancer patients.

Mutations in certain genes that regulate the cell cycle, such as p16 and p53, are frequently found in human cancers. However, tumor-specific mutations are uncommon in genes encoding cyclin E and the CDK inhibitor p27Kip1, two cell-cycle regulators that are also thought to contribute to tumor progression. It is now known that levels of both cyclin E and p27 can be controlled by posttranscriptional mechanisms, indicating that expression of these proteins can be altered by means other than simply mutation of their respective genes. Thus, changes in p27 and cyclin E protein levels in tumors might be more common than previously anticipated and may be indicators of tumor behavior.

Adult↗

PubMedDate not supplied

Heart, body, and soul: impact of church-based smoking cessation interventions on readiness to quit.

BACKGROUND: Given the relatively low spontaneous quit rates and poor treatment outcomes among African American smokers, this study was designed to evaluate the effects of a multimodal culturally relevant intervention for smoking behavior change compared with a self-help strategy among urban African Americans in Baltimore churches. METHOD: This randomized controlled trial in urban African American churches used the stages of change model to compare the effectiveness of two interventions in moving smokers along a continuum toward smoking cessation. Twenty-two churches were randomly assigned to either an intensive culturally specific intervention or a minimal self-help intervention. Smokers were interviewed at baseline church health fairs and at a 1-year follow-up. Self-reported quitters at follow-up were evaluated using saliva cotinine and exhaled carbon monoxide levels (CO). Stages of change were measured by applying a standardized stages of change instrument to individual interview response sequences. Analysis compared the two intervention groups at 1-year follow-up with baseline stages. Outcomes included quit rates and positive progress along the stages of change. RESULTS: Multiple logistic regression results, controlling for intrachurch correlation and demographic and baseline smoking characteristics, showed that the multimodal cultural intervention group was more likely to make positive progress along the stages of change continuum, compared with self-help intervention group (OR = 1.68; P = 0.04). Church denomination and intervention status interacted in the multivariate model; Baptists in the intensive intervention were three times (OR = 3.23; P = 0.010) more likely to make progress than all the other denomination groups. CONCLUSION: The multimodal culturally relevant intervention was more likely than a self-help intervention to positively influence smoking behavior. This is the first community-based intervention study to report progress along the stages of change as a process-oriented measure of success. It is notable that a spiritually based model focusing on environmental sanctions was more likely than a standard church disseminated self-help intervention to positively influence smoking behavior in an urban African American population.

Adult↗

PubMedDate not supplied

Can evidence change the rate of back surgery? A randomized trial of community-based education.

CONTEXT: Timely adoption of clinical practice guidelines is more likely to happen when the guidelines are used in combination with adjuvant educational strategies that address social as well as rational influences. OBJECTIVE: To implement the conservative, evidence-based approach to low-back pain recommended in national guidelines, with the anticipated effect of reducing population-based rates of surgery. DESIGN: A randomized, controlled trial. SETTING: Ten communities in western Washington State with annual rates of back surgery above the 1990 national average (158 operations per 100,000 adults). PARTICIPANTS: Spine surgeons, primary care physicians, patients who were surgical candidates, and hospital administrators. INTERVENTION: The five communities randomized to the intervention group received a package of six educational activities tailored to local needs by community planning groups. Surgeon study groups, primary care continuing medical education conferences, administrative consensus processes, videodisc-aided patient decision making, surgical outcomes management, and generalist academic detailing were serially implemented over a 30-month intervention period. OUTCOME MEASURE: Quarterly observations of surgical rates. RESULTS: After implementation of the intervention, surgery rates declined in the intervention communities but increased slightly in the control communities. The net effect of the intervention is estimated to be a decline of 20.9 operations per 100,000, a relative reduction of 8.9% (P = 0.01). CONCLUSION: We were able to use scientific evidence to engender voluntary change in back pain practice patterns across entire communities.

Education, Medical, Continuing↗