Initial Validation of a Computerized Adaptive Test for Substance Use Disorder Identification in Adolescents.

PURPOSE: Computerized adaptive tests (CATs) are highly efficient assessment tools that couple low patient and clinician time burden with high diagnostic accuracy. A CAT for substance use disorders (CAT-SUD-E) has been validated in adult populations but has yet to be tested in adolescents. The purpose of this study was to perform initial evaluation of the K-CAT-SUD-E (i.e., Kiddy-CAT-SUD-E) in an adolescent sample compared to a gold-standard diagnostic interview. METHODS: Adolescents (N = 156; aged 11-17) with diverse substance use histories completed the K-CAT-SUD-E electronically and the substance related disorders portion of a clinician-conducted diagnostic interview (K-SADS) via tele-videoconferencing platform. The K-CAT-SUD-E assessed both current and lifetime overall SUD and substance-specific diagnoses for nine substance classes. RESULTS: Using the K-CAT-SUD-E continuous severity score and diagnoses to predict the presence of any K-SADS SUD diagnosis, the classification accuracy ranged from excellent for current SUD (AUC = 0.89, 95% CI = 0.81, 0.95) to outstanding (AUC = 0.93, 95% CI = 0.82, 0.97) for lifetime SUD. Regarding current substance-specific diagnoses, the classification accuracy was excellent for alcohol (AUC = 0.82), cannabis (AUC = 0.83) and nicotine/tobacco (AUC = 0.90). For lifetime substance-specific diagnoses, the classification accuracy ranged from excellent (e.g., opioids, AUC = 0.84) to outstanding (e.g., stimulants, AUC = 0.96). K-CAT-SUD-E median completion time was 4 min 22 s compared to 45 min for the K-SADS. CONCLUSIONS: This study provides initial support for the K-CAT-SUD-E as a feasible accurate diagnostic tool for assessing SUDs in adolescents. Future studies should further validate the K-CAT-SUD-E in a larger sample of adolescents and examine its acceptability, feasibility, and scalability in youth-serving settings.

Radiological risk assessment of the Hunters Point Naval Shipyard (HPNS).

Hunters Point Naval Shipyard in San Francisco, California was deemed a Superfund site by the USEPA in 1989 due to chemical and radiological contamination resulting from U.S. Navy operations from 1939 to 1974. During characterization and remediation efforts, over 50,000 radiological soil samples and 19,000 air samples were collected. This risk assessment, conducted in accordance with federal guidelines, represents the first comprehensive evaluation of past, present, and future health risks associated with radionuclides present at the site. The assessment indicated that before site remediation, most radionuclide soil concentrations were at or near local background concentrations. Had such low remedial goals not been established, significant remediation of surface soils would not have been necessary to protect human health. The pre-remediation lifetime incremental cancer morbidity risks for on-site workers and theoretical on-site residents due to radionuclide contamination were found to be 1.3 × 10-6 and 3.2 × 10-6, respectively. The post-remediation risks to future on-site residents were found to be 6.3 × 10-8 (without durable cover) and 3.7 × 10-8 (with durable cover), while post-remediation risks to on-site workers were found to be 2.6 × 10-8 (without durable cover) and 1.6 × 10-8 (with durable cover). Risk estimates for all scenarios were found to be significantly below the acceptable risk of 3 × 10-4 approved by regulatory agencies. Upwind and downwind air samples collected during remediation indicate that remediation activities never posed a measurable risk to off-site residents. This risk assessment emphasizes the importance of establishing clear and scientifically rigorous soil remedial goals at sites as well as understanding local radionuclide background concentrations.

Development of a computerized adaptive substance use disorder scale for screening, measurement and diagnosis - The CAT-SUD-E.

Introduction: The Computerized Adaptive Test for Substance Use Disorder (CAT-SUD), an adaptive test based on multidimensional item response theory, has been expanded to include 7 specific Diagnostic and Statistical Manual, 5th edition (DSM-5) defined SUDs. Initial testing of the new measure, the CAT-SUD expanded (CAT-SUD-E) is reported here. Methods: 275 Community-dwelling adults (ages 18-68) responded to public and social-media advertisements. Participants virtually completed both the CAT-SUD-E and the Structured Clinical Interview for DSM-5, Research Version (SCID) to assess the validity of the CAT-SUD-E in determining whether participants met criteria for specific DSM-5 SUDs. Diagnostic classifications were based on 7 SUDs, each with 5 items, for current and lifetime SUDs. Results: For SCID-based presence of any lifetime SUD, predictions based on the overall CAT-SUD-E diagnosis and severity score were AUC=0.92, 95% CI = 0.88, 0.95 for current and AUC=0.94, 95% CI = 0.91, 0.97 for lifetime. For individual diagnoses, classification accuracy for current SUDs ranged from an AUC=0.76 for alcohol to AUC=0.92 for nicotine/tobacco. Classification accuracy for lifetime SUDs ranged from an AUC=0.81 for hallucinogens to AUC=0.96 for stimulants. Median CAT-SUD-E completion time was under 4 min. Conclusions: The CAT-SUD-E quickly produces similar results as lengthy structured clinical interviews for overall SUD and substance-specific SUDs, with high precision and accuracy, through a combination of fixed-item responses for diagnostic classification and adaptive SUD severity measurement. The CAT-SUD-E harmonizes information from mental health, trauma, social support and traditional SUD items to provide a more complete characterization of SUD and provides both diagnostic classification and severity measurement.

Preoperative Assessment of Anxiety and Depression Using Computerized Adaptive Screening Tools: A Pilot Prospective Cohort Study.

BACKGROUND: Serious mental health conditions (eg, anxiety and depression) are common in surgical patients, yet likely underassessed due to the time-consuming and cumbersome traditional screening process. A recently developed computerized adaptive mental health assessment tool (computerized adaptive test-mental health [CAT-MH]) allows rapid, precise, and accurate assessment of numerous mental health disorders, including anxiety and depression, without the need for a trained interviewer. The goal of this investigation was to determine the feasibility of administering CAT-MH for anxiety and depression in the preoperative setting and to obtain preliminary evidence of the prevalence of anxiety and depression in preoperative patients. METHODS: In this prospective cohort study, 100 adult patients scheduled for elective surgery were enrolled and asked to complete the CAT-MH in the preoperative clinic. Urgent and emergency surgeries were excluded as were pregnant patients. Primary feasibility outcomes were completion rate and time to completion. Secondary outcomes were prevalence estimates of anxiety and depression. RESULTS: All 100 enrolled patients completed the study. All patients were able to complete the mental health assessment (mean time: 3.6 ± 1.8 minutes standard deviation). Sixteen patients (16%) screened positive for anxiety (severity: mild, n = 7 [7%]; moderate, n = 7 [7%]); severe, n = 2 [2%]); 12 of 16 (75%) did not have a previous diagnosis of anxiety disorder. Twenty-eight (28%) patients screened positive for depression (severity: mild, n = 26 [26%]; moderate and severe, n = 1 each [1%]); 23 of 28 (82%) had no previous diagnosis of depressive disorder. Nineteen patients (19%) met the screening criteria for major depressive disorder; 14 of 19 (74%) of which had no previous diagnosis of major depressive disorder. CONCLUSIONS: The results of this pilot study support the feasibility of using CAT-MH in a preoperative evaluation and indicate that there is a substantial prevalence of undiagnosed anxiety and depression in surgical patients.

Development and Validation of Computerized Adaptive Assessment Tools for the Measurement of Posttraumatic Stress Disorder Among US Military Veterans.

Importance: Veterans from recent and past conflicts have high rates of posttraumatic stress disorder (PTSD). Adaptive testing strategies can increase accuracy of diagnostic screening and symptom severity measurement while decreasing patient and clinician burden. Objective: To develop and validate a computerized adaptive diagnostic (CAD) screener and computerized adaptive test (CAT) for PTSD symptom severity. Design, Setting, and Participants: A diagnostic study of measure development and validation was conducted at a Veterans Health Administration facility. A total of 713 US military veterans were included. The study was conducted from April 25, 2017, to November 10, 2019. Main Outcomes and Measures: The participants completed a PTSD-symptom questionnaire from the item bank and provided responses on the PTSD Checklist for Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) (PCL-5). A subsample of 304 participants were interviewed using the Clinician-Administered Scale for PTSD for DSM-5. Results: Of the 713 participants, 585 were men; mean (SD) age was 52.8 (15.0) years. The CAD-PTSD reproduced the Clinician-Administered Scale for PTSD for DSM-5 PTSD diagnosis with high sensitivity and specificity as evidenced by an area under the curve of 0.91 (95% CI, 0.87-0.95). The CAT-PTSD demonstrated convergent validity with the PCL-5 (r = 0.88) and also tracked PTSD diagnosis (area under the curve = 0.85; 95% CI, 0.79-0.89). The CAT-PTSD reproduced the final 203-item bank score with a correlation of r = 0.95 with a mean of only 10 adaptively administered items, a 95% reduction in patient burden. Conclusions and Relevance: Using a maximum of only 6 items, the CAD-PTSD developed in this study was shown to have excellent diagnostic screening accuracy. Similarly, using a mean of 10 items, the CAT-PTSD provided valid severity ratings with excellent convergent validity with an extant scale containing twice the number of items. The 10-item CAT-PTSD also outperformed the 20-item PCL-5 in terms of diagnostic accuracy. The results suggest that scalable, valid, and rapid PTSD diagnostic screening and severity measurement are possible.

Validation of the Computerized Adaptive Test for Mental Health in Primary Care.

PURPOSE: The US Preventive Services Task Force recommends screening for depression in the general adult population. Although screening questionnaires for depression and anxiety exist in primary care settings, electronic health tools such as computerized adaptive tests based on item response theory can advance screening practices. This study evaluated the validity of the Computerized Adaptive Test for Mental Health (CAT-MH) for screening for major depressive disorder (MDD) and assessing MDD and anxiety severity among adult primary care patients. METHODS: We approached 402 English-speaking adults for participation from a primary care clinic, of whom 271 adults (71% female, 65% black) participated. Participants completed modules from the CAT-MH (Computerized Adaptive Diagnostic Test for MDD, CAT-Depression Inventory, CAT-Anxiety Inventory); brief paper questionnaires (9-item Patient Health Questionnaire [PHQ-9], 2-item Patient Health Questionnaire [PHQ-2], Generalized Anxiety Disorder 7-item Scale [GAD-7]); and a reference-standard interview, the Structured Clinical Interview for DSM-5 (Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition) Diagnoses. RESULTS: On the basis of the interview, 31 participants met criteria for MDD and 29 met criteria for GAD. The diagnostic accuracy of the Computerized Adaptive Diagnostic Test for MDD (area under curve [AUC] = 0.85) was similar to that of the PHQ-9 (AUC = 0.84) and higher than that of the PHQ-2 (AUC = 0.76) for MDD screening. Using the interview as the reference standard, the accuracy of the CAT-Anxiety Inventory (AUC = 0.93) was similar to that of the GAD-7 (AUC = 0.97) for assessing anxiety severity. The patient-preferred screening method was assessment via tablet/computer with audio. CONCLUSIONS: Computerized adaptive testing could be a valid and efficient patient-centered screening strategy for depression and anxiety screening in primary care settings.

Association of Mental Health Conditions and Treatments With Long-term Opioid Analgesic Receipt Among Adolescents.

Importance: Adults with mental health conditions are more likely than those without to receive long-term opioid therapy. Less is known about opioid therapy among adolescents, especially those with mental health conditions. Objective: To examine associations between preexisting mental health conditions and treatments and initiation of any opioid and long-term opioid therapy among adolescents. Design, Setting, and Participants: A cohort of 1 224 520 incident opioid recipients without cancer diagnoses aged 14 to 18 years at first receipt was extracted from nationwide commercial health care claims data from January 1, 2003, to December 31, 2014. Analysis was conducted from August 19, 2016, to November 16, 2017. Associations between preexisting mental health conditions and treatments and any opioid receipt were examined by comparing recipients with nonrecipients matched on sex, calendar year and years of age of first enrollment, and months of enrollment (prior to the index month for recipients, ever for nonrecipients). Associations between preexisting mental health conditions and treatments and subsequent long-term opioid therapy were examined among recipients with at least 6 months' follow-up using Cox proportional hazards regressions adjusted for demographics. Exposures: Mental health condition diagnoses and treatments recorded in inpatient, outpatient, and filled-prescription claims prior to opioid receipt. Main Outcomes and Measures: Opioid receipt, defined as any opioid analgesic prescription claim, and long-term opioid therapy, defined as more than 90 days' supply within a 6-month window having no gaps in supply of more than 32 days. Results: Of the 1 224 520 new opioid recipients included, the median age at first receipt was 17 years (interquartile range, 16-18 years), and 51.1% were female. Median follow-up after first receipt was 625 days (interquartile range, 255-1268 days). Adolescents with anxiety, mood, neurodevelopmental, sleep, and nonopioid substance use disorders and most mental health treatments were significantly more likely to receive any opioid (odds ratios from 1.13 [95% CI, 1.10-1.16] for nonopioid substance use disorders to 1.69 [95% CI, 1.58-1.81] for nonbenzodiazepine hypnotics). Among the 1 000 453 opioid recipients (81.7%) who had at least 6 months' follow-up, the cumulative incidence of long-term opioid therapy was 3.0 (95% CI, 2.8-3.1) per 1000 recipients within 3 years after first opioid receipt. All preexisting mental health conditions and treatments were strongly associated with higher rates of long-term opioid therapy (adjusted hazard ratios from 1.73 [95% CI 1.54-1.95] for attention-deficit/hyperactivity disorder to 8.90 [95% CI, 5.85-13.54] for opioid use disorder). Conclusions and Relevance: Commercially insured adolescents with many types of preexisting mental health conditions and treatments were modestly more likely to receive any opioid and were substantially more likely to subsequently transition to long-term opioid therapy relative to those without, although overall rates of long-term opioid therapy were low.

A note on marginalization of regression parameters from mixed models of binary outcomes.

This article discusses marginalization of the regression parameters in mixed models for correlated binary outcomes. As is well known, the regression parameters in such models have the "subject-specific" (SS) or conditional interpretation, in contrast to the "population-averaged" (PA) or marginal estimates that represent the unconditional covariate effects. We describe an approach using numerical quadrature to obtain PA estimates from their SS counterparts in models with multiple random effects. Standard errors for the PA estimates are derived using the delta method. We illustrate our proposed method using data from a smoking cessation study in which a binary outcome (smoking, Y/N) was measured longitudinally. We compare our estimates to those obtained using GEE and marginalized multilevel models, and present results from a simulation study.

Development of the ThyCAT: A clinically useful computerized adaptive test to assess quality of life in thyroid cancer survivors.

BACKGROUND: Current quality of life assessment tools for thyroid cancer survivors are not clinically useful due to the length of available questionnaires. Computerized adaptive tests are easily administered electronically and can achieve highly accurate and efficient results in minimal time. We aimed to develop a quality of life computerized adaptive tests (ThyCAT) for thyroid cancer survivors. METHODS: A bifactor item response theory model was fit to questionnaire responses from 1,078 North American Thyroid Cancer Survivorship Study participants-a longitudinal cohort study of quality of life in thyroid cancer survivors. Tuning parameters were selected to maintain a correlation of r > 0.9 with the total item bank quality of life score obtained from the original North American Thyroid Cancer Survivorship Study questions, using a minimal number of adaptively administered ThyCAT items. RESULTS: The ThyCAT assesses quality of life with strong correlation (r = 0.96) with the original 75 North American Thyroid Cancer Survivorship Study questions using an average of 9.94 questions (SD ± 3.03) administered in <2 minutes. There was no statistically significant difference in the number of ThyCAT questions required based on demographic or tumor characteristics. CONCLUSION: The ThyCAT can be administered on a smartphone app in <10 questions, and <2 minutes, allowing efficient and accurate in or out of clinic identification of patients struggling with quality of life issues after thyroid cancer treatment.

Incident and long-term opioid therapy among patients with psychiatric conditions and medications: a national study of commercial health care claims.

There is growing evidence that opioid prescribing in the United States follows a pattern in which patients who are at the highest risk of adverse outcomes from opioids are more likely to receive long-term opioid therapy. These patients include, in particular, those with substance use disorders (SUDs) and other psychiatric conditions. This study examined health insurance claims among 10,311,961 patients who filled prescriptions for opioids. Specifically, we evaluated how opioid receipt differed among patients with and without a wide range of preexisting psychiatric and behavioral conditions (ie, opioid and nonopioid SUDs, suicide attempts or other self-injury, motor vehicle crashes, and depressive, anxiety, and sleep disorders) and psychoactive medications (ie, antidepressants, benzodiazepines, hypnotics, mood stabilizers, antipsychotics, and medications used for SUD, tobacco cessation, and attention-deficit/hyperactivity disorder). Relative to those without, patients with all assessed psychiatric conditions and medications had modestly greater odds of subsequently filling prescriptions for opioids and, in particular, substantially greater risk of long-term opioid receipt. Increases in risk for long-term opioid receipt in adjusted Cox regressions ranged from approximately 1.5-fold for prior attention-deficit/hyperactivity disorder medication prescriptions (hazard ratio [HR] = 1.53; 95% confidence interval [CI], 1.48-1.58) to approximately 3-fold for prior nonopioid SUD diagnoses (HR = 3.15; 95% CI, 3.06-3.24) and nearly 9-fold for prior opioid use disorder diagnoses (HR = 8.70; 95% CI, 8.20-9.24). In sum, we found evidence of greater opioid receipt among commercially insured patients with a breadth of psychiatric conditions. Future studies assessing behavioral outcomes associated with opioid prescribing should consider preexisting psychiatric conditions.

Characterizing the pain score trajectories of hospitalized adult medical and surgical patients: a retrospective cohort study.

Pain care for hospitalized patients is often suboptimal. Representing pain scores as a graphical trajectory may provide insights into the understanding and treatment of pain. We describe a 1-year, retrospective, observational study to characterize pain trajectories of hospitalized adults during the first 48 hours after admission at an urban academic medical center. Using a subgroup of patients who presented with significant pain (pain score >4; n = 7762 encounters), we characterized pain trajectories and measured area under the curve, slope of the trajectory for the first 2 hours after admission, and pain intensity at plateau. We used mixed-effects regression to assess the association between pain score and sociodemographics (age, race, and gender), pain medication orders (opioids, nonopioids, and no medications), and medical service (obstetrics, psychiatry, surgery, sickle cell, intensive care unit, and medicine). K-means clustering was used to identify patient subgroups with similar trajectories. Trajectories showed differences based on race, gender, service, and initial pain score. Patients presumed to have dissimilar pain experiences (eg, sickle vs obstetrical) had markedly different pain trajectories. Patients with higher initial pain had a more rapid reduction during their first 2 hours of treatment. Pain reduction achieved in the 48 hours after admission was approximately 50% of the initial pain, regardless of the initial pain. Most patients' pain failed to fully resolve, plateauing at a pain score of 4 or greater. Visualizing pain scores as graphical trajectories illustrates the dynamic variability in pain, highlighting pain responses over a period of observation, and may yield new insights for quality improvement and research.

Varenicline, smoking cessation, and neuropsychiatric adverse events.

OBJECTIVE: In 2009, the U.S. Food and Drug Administration issued a black box warning for varenicline regarding neuropsychiatric events. The authors used data from randomized controlled trials and from a large Department of Defense (DOD) observational study to assess the efficacy and safety of varenicline. METHOD: The authors reanalyzed data from the 17 placebo-controlled randomized controlled trials (N=8,027) of varenicline conducted by Pfizer, using complete intent-to-treat person-level longitudinal data to assess smoking abstinence and reports of suicidal thoughts and behavior, depression, aggression/agitation, and nausea and to compare effects in patients with (N=1,004) and without (N=7,023) psychiatric disorders. The authors also analyzed a large DOD data set to compare acute (30-day and 60-day) rates of neuropsychiatric adverse events in patients receiving varenicline or nicotine replacement therapy (N=35,800) and to assess reports of anxiety, mood, and psychotic symptoms and disorders, other mental disorders, and suicide attempt. RESULTS: In the randomized controlled trials, varenicline increased the risk of nausea (odds ratio=3.69, 95% CI=3.03-4.48) but not rates of suicidal events, depression, or aggression/agitation. It significantly increased the abstinence rate, by 124% compared with placebo and 22% compared with bupropion. Having a current or past psychiatric illness increased the risk of neuropsychiatric events equally in treated and placebo patients. In the DOD study, after propensity score matching, the overall rate of neuropsychiatric disorders was significantly lower for varenicline than for nicotine replacement therapy (2.28% compared with 3.16%). CONCLUSIONS: This analysis revealed no evidence that varenicline is associated with adverse neuropsychiatric events. The evidence supports the superior efficacy of varenicline relative to both placebo and bupropion, indicating considerable benefit without evidence of risk of serious neuropsychiatric adverse events, in individuals with and without a recent history of a psychiatric disorder.

The computerized adaptive diagnostic test for major depressive disorder (CAD-MDD): a screening tool for depression.

OBJECTIVE: To develop a computerized adaptive diagnostic screening tool for depression that decreases patient and clinician burden and increases sensitivity and specificity for clinician-based DSM-IV diagnosis of major depressive disorder (MDD). METHOD: 656 individuals with and without minor and major depression were recruited from a psychiatric clinic and a community mental health center and through public announcements (controls without depression). The focus of the study was the development of the Computerized Adaptive Diagnostic Test for Major Depressive Disorder (CAD-MDD) diagnostic screening tool based on a decision-theoretical approach (random forests and decision trees). The item bank consisted of 88 depression scale items drawn from 73 depression measures. Sensitivity and specificity for predicting clinician-based Structured Clinical Interview for DSM-IV Axis I Disorders diagnoses of MDD were the primary outcomes. Diagnostic screening accuracy was then compared to that of the Patient Health Questionnaire-9 (PHQ-9). RESULTS: An average of 4 items per participant was required (maximum of 6 items). Overall sensitivity and specificity were 0.95 and 0.87, respectively. For the PHQ-9, sensitivity was 0.70 and specificity was 0.91. CONCLUSIONS: High sensitivity and reasonable specificity for a clinician-based DSM-IV diagnosis of depression can be obtained using an average of 4 adaptively administered self-report items in less than 1 minute. Relative to the currently used PHQ-9, the CAD-MDD dramatically increased sensitivity while maintaining similar specificity. As such, the CAD-MDD will identify more true positives (lower false-negative rate) than the PHQ-9 using half the number of items. Inexpensive (relative to clinical assessment), efficient, and accurate screening of depression in the settings of primary care, psychiatric epidemiology, molecular genetics, and global health are all direct applications of the current system.

Development of a computerized adaptive test for depression.

CONTEXT Unlike other areas of medicine, psychiatry is almost entirely dependent on patient report to assess the presence and severity of disease; therefore, it is particularly crucial that we find both more accurate and efficient means of obtaining that report. OBJECTIVE To develop a computerized adaptive test (CAT) for depression, called the Computerized Adaptive Test-Depression Inventory (CAT-DI), that decreases patient and clinician burden and increases measurement precision. DESIGN Case-control study. SETTING A psychiatric clinic and community mental health center. PARTICIPANTS A total of 1614 individuals with and without minor and major depression were recruited for study. MAIN OUTCOME MEASURES The focus of this study was the development of the CAT-DI. The 24-item Hamilton Rating Scale for Depression, Patient Health Questionnaire 9, and the Center for Epidemiologic Studies Depression Scale were used to study the convergent validity of the new measure, and the Structured Clinical Interview for DSM-IV was used to obtain diagnostic classifications of minor and major depressive disorder. RESULTS A mean of 12 items per study participant was required to achieve a 0.3 SE in the depression severity estimate and maintain a correlation of r = 0.95 with the total 389-item test score. Using empirically derived thresholds based on a mixture of normal distributions, we found a sensitivity of 0.92 and a specificity of 0.88 for the classification of major depressive disorder in a sample consisting of depressed patients and healthy controls. Correlations on the order of r = 0.8 were found with the other clinician and self-rating scale scores. The CAT-DI provided excellent discrimination throughout the entire depressive severity continuum (minor and major depression), whereas the traditional scales did so primarily at the extremes (eg, major depression). CONCLUSIONS Traditional measurement fixes the number of items administered and allows measurement uncertainty to vary. In contrast, a CAT fixes measurement uncertainty and allows the number of items to vary. The result is a significant reduction in the number of items needed to measure depression and increased precision of measurement.

Advances in analysis of longitudinal data.

In this review, we explore recent developments in the area of linear and nonlinear generalized mixed-effects regression models and various alternatives, including generalized estimating equations for analysis of longitudinal data. Methods are described for continuous and normally distributed as well as categorical (binary, ordinal, nominal) and count (Poisson) variables. Extensions of the model to three and four levels of clustering, multivariate outcomes, and incorporation of design weights are also described. Linear and nonlinear models are illustrated using an example involving a study of the relationship between mood and smoking.

Biomarkers Predict p53 Gene Therapy Efficacy in Recurrent Squamous Cell Carcinoma of the Head and Neck.

PURPOSE: Most recurrent squamous cell carcinomas of the head and neck have a dysfunctional p53 tumor suppressor pathway contributing to treatment resistance. We hypothesized that tumor p53 biomarkers may predict the efficacy of normal p53 delivered by gene therapy in these patients. EXPERIMENTAL DESIGN: Tumor p53 biomarkers were evaluated in 116 patients, including 29 treated with methotrexate in a phase III randomized controlled trial. Profiles favorable for p53 gene therapy efficacy were hypothesized to have either normal p53 gene sequences or low-level p53 protein expression, whereas unfavorable p53 inhibitor profiles were predicted to have high-level expression of mutated p53 that can inhibit normal p53 protein function. RESULTS: A statistically significant increase in tumor responses was observed for patients with favorable p53 efficacy profiles compared with those with unfavorable p53 inhibitor profiles [phase I/II trials: favorable (34 of 46, 74%) versus unfavorable (1 of 5, 20%), P = 0.0290; phase III trial: favorable (17 of 24, 71%) versus unfavorable (2 of 11, 18%), P = 0.0088]. In the phase III trial, there was statistically significant increased time to progression (TTP) and survival following p53 gene therapy in patients with favorable p53 profiles compared with unfavorable p53 inhibitor profiles (median TTP, 2.7 months versus 1.4 months, P = 0.0121; median survival, 7.2 months versus 2.7 months, P < 0.0001). In contrast, the biomarker profiles predictive of p53 gene therapy efficacy did not predict methotrexate response, TTP, or survival outcomes. CONCLUSIONS: These results indicate that tumor p53 biomarker profiles may predict p53 gene therapy efficacy in recurrent squamous cell carcinoma of the head and neck. (Clin Cancer Res 2009;15(24):7719-25).

Survival of primary and repeat lung transplantation in the United States.

BACKGROUND: This study was undertaken to compare survival between primary and repeat lung transplant recipients and to identify survival predictors after repeat lung transplantation. METHODS: Data for 10,846 primary and 354 repeat lung transplant patients were extracted from the United Network for Organ Sharing registry. Propensity score matching was used to examine balance in the distribution of potential observed confounders and to match the sample in terms of the probability of repeat lung transplantation given pretransplant characteristics alone. Matching based on the propensity score was used to compare survival between the primary and repeat lung transplant groups. A Cox regression model was used to identify risk factors for death in the cohort of patients receiving lung transplant. RESULTS: Considerable bias between the primary and repeat lung transplant groups was found in the sample. Patients with high propensity scores tended to carry high-risk profiles. Propensity score matching revealed incomplete overlap of covariate distributions between primary and repeat transplant groups. For those subjects who could be matched for the set of potential confounding variables, no difference in survival time was observed between primary and repeat lung transplant patients. Functional status and serum creatinine level were the two clinically important risk factors for predicting the survival of repeat transplant patients. CONCLUSIONS: The current study revealed that direct comparison of the survival of primary and repeat lung transplant patients is biased by nonoverlap in the distribution of potential confounders. Using propensity score matching we adjusted for this bias and found that there was no significant difference in survival between first and second transplants.

Repeat heart-lung transplantation outcome in the United States.

OBJECTIVES: This study compared risk-adjusted survival between primary and repeat heart-lung transplantation. METHODS: Data for 799 primary heart-lung and 19 repeat heart-lung transplants were extracted from the United Network Organ Sharing (UNOS) registry. Analyses were based on propensity score matching in which 1, 2, and 3 primary transplant patients were matched with 19 repeat transplant patients. The matching variables were sex of recipient and donor, ethnicity, race, age of recipient and donor, cytomegalovirus status, ABO match, human leukocyte antigen mismatch, medical condition (hospitalized), ventilator, employment status, functional status, UNOS transplant status, and ischemic time. RESULTS: Propensity score matching revealed incomplete overlap of covariate distributions between primary and repeat transplant patients. The 19 repeat heart-lung transplant patients were more severely impaired at the time of transplant, and 4 did not have an adequate primary transplant match. For 15 repeat transplant patients, survival time was not significantly different from matched primary transplant controls. For repeat transplant patients, being Hispanic, having longer ischemic time, poor functional status (needing assistance), being hospitalized, and requiring ventilator support were all associated with decreased survival time; however, only being on a ventilator was statistically significant. By contrast, being female, and younger were associated with increased survival, but were not statistically significant. CONCLUSIONS: When matched for a set of potential confounding variables, no difference in survival benefit was observed between primary and repeat heart-lung transplant patients. The only predictor significantly associated with decreased survival time among repeat transplant patients was being on a ventilator.

Comparison of survival in primary and repeat heart transplantation from 1987 through 2004 in the United States.

BACKGROUND: The purpose of this study was to identify predictors for survival after primary and repeat heart transplantations, and to compare their survival. METHODS: The United Network for Organ Sharing database provided 20,787 primary heart transplants and 594 repeat heart transplants (for those patients who had previously undergone a primary heart transplant). Cox regression models were used to separately determine predictors of survival in primary and retransplant patients and to compare their survival distributions. Propensity score matching was then used to compare the survival between primary and retransplant patients adjusted for potential confounders. RESULTS: Similar predictors of survival were found for primary and retransplant patients. The overall increased risk of death was 71% higher for retransplant versus primary transplant patients. Propensity score analysis showed that, in patients with characteristics most similar to primary transplant patients, the increased risk of death was 133%; however, for patients with characteristics most like retransplant patients, the increased risk of death was only 34%. CONCLUSIONS: Survival after retransplantation is significantly reduced relative to survival after primary transplantation. The difference in survival between primary and repeat transplants is smallest among recipients who fit the profile of the typical repeat transplant patient. In general, these are younger patients with better functional status prior to listing, who received an organ from a younger donor.