New Sequential Approximation Method

Statistic

Methodological issues in assessing changes in costs pre- and post-medication switch: a schizophrenia study example

<p>Abstract</p> <p>Background</p> <p>Schizophrenia is a severe, chronic, and costly illness that adversely impacts patients' lives and health care payer budgets. Cost comparisons of treatment regimens are, therefore, important to health care payers and researchers. Pre-Post analyses ("mirror-image"), where outcomes prior to a medication switch are compared to outcomes post-switch, are commonly used in such research. However, medication changes often occur during a costly crisis event. Patients may relapse, be hospitalized, have a medication change, and then spend a period of time with intense use of costly resources (post-medication switch). While many advantages and disadvantages of Pre-Post methodology have been discussed, issues regarding the attributability of costs incurred around the time of medication switching have not been fully investigated.</p> <p>Methods</p> <p>Medical resource use data, including medications and acute-care services (hospitalizations, partial hospitalizations, emergency department) were collected for patients with schizophrenia who switched antipsychotics (n = 105) during a 1-year randomized, naturalistic, antipsychotic cost-effectiveness schizophrenia trial. Within-patient changes in total costs per day were computed during the pre- and post-medication change periods. In addition to the standard Pre-Post analysis comparing costs pre- and post-medication change, we investigated the sensitivity of results to varying assumptions regarding the attributability of acute care service costs occurring just after a medication switch that were likely due to initial medication failure.</p> <p>Results</p> <p>Fifty-six percent of all costs incurred during the first week on the newly initiated antipsychotic were likely due to treatment failure with the previous antipsychotic. Standard analyses suggested an average increase in cost-per-day for each patient of $2.40 after switching medications. However, sensitivity analyses removing costs incurred post-switch that were potentially due to the failure of the initial medication suggested decreases in costs in the range of$4.77 to $9.69 per day post-switch.</p> <p>Conclusion</p> <p>Pre-Post cost analyses are sensitive to the approach used to handle acute-service costs occurring just after a medication change. Given the importance of quality economic research on the cost of switching treatments, thorough sensitivity analyses should be performed to identify the impact of crisis events around the time of medication change.</p

Adherence and persistence with branded antidepressants and generic SSRIs among managed care patients with major depressive disorder

Xianchen Liu1,2, Yi Chen3, Douglas E Faries31Former employee, Eli Lilly and Company, Indianapolis, Indiana, USA; 2Indiana University Department of Psychiatry, Indianapolis, Indiana, USA; 3Eli Lilly and Company, Indianapolis, Indiana, USAObjective: This study compared adherence and persistence of three branded antidepressants: the serotonin and norepinephrine reuptake inhibitors (SNRIs) duloxetine and venlafaxine XR, and the selective serotonin reuptake inhibitor (SSRI) escitalopram; and generic selective SSRIs, and examined demographic and clinical predictors of adherence and persistence in patients with major depressive disorder in usual care settings.Method: A total of 44,026 patients (18 to 64 years) from a large commercial administrative claims database were classified as initiators of duloxetine (n = 7,567), venlafaxine XR (n = 6,106), escitalopram (n = 10,239), or generic SSRIs (n = 20,114) during 2006. Adherence was defined as the medication possession ratio of &amp;ge; 0.8 and persistence as the length of therapy without exceeding a 15-day gap. Pairwise comparisons from multivariate logistic regression and Cox proportional hazards models were performed to examine predictors of adherence and persistence.Results: Adherence rate after one year was significantly higher in duloxetine recipients (38.1%) than patients treated with venlafaxine XR (34.0%), escitalopram (25.4%), or generic SSRIs (25.5%) (all P &amp;lt; 0.01). Duloxetine recipients stayed on medication longer (158.5 days) than those receiving venlafaxine XR (149.6 days), escitalopram (129.1 days), or generic SSRIs (130.2 days) (all P &amp;lt; 0.001). Compared with patients treated with escitalopram or generic SSRIs, venlafaxine XR recipients had better adherence and longer persistence (P &amp;lt; 0.001). In addition, being aged 36 years or more, hypersomnia, anxiety disorders, and prior use of antidepressants were associated with increased adherence and persistence, while the opposite was true for comorbid chronic pain conditions, alcohol and drug dependence, and prior use of amphetamine.Conclusion: Compared with SSRIs, the SNRIs appear to have better adherence and persistence. Among SNRIs, duloxetine had statistically significantly better adherence and persistence than venlafaxine XR, though differences were relatively small and further research is needed to assess whether these translate into clinically and economically meaningful outcomes. Adherence and persistence with antidepressant therapy were associated with age, multiple comorbid conditions, and prior use of medications.Keywords: treatment adherence, length of therapy, antidepressants, major depression, retrospective analysi

A comparison of olanzapine and risperidone on the risk of psychiatric hospitalization in the naturalistic treatment of patients with schizophrenia

BACKGROUND: Decreasing hospital admissions is important for improving outcomes for people with schizophrenia and for reducing cost of hospitalization, the largest expenditure in treating this persistent and severe mental illness. This prospective observational study compared olanzapine and risperidone on one-year psychiatric hospitalization rate, duration, and time to hospitalization in the treatment of patients with schizophrenia in usual care. METHODS: We examined data of patients newly initiated on olanzapine (N = 159) or risperidone (N = 112) who continued on the index antipsychotic for at least one year following initiation. Patients were participants in a 3-year prospective, observational study of schizophrenia patients in the US. Outcome measures were percent of hospitalized patients, total days hospitalized per patient, and time to first hospitalization during the one-year post initiation. Analyses employed a generalized linear model with adjustments for demographic and clinical variables. A two-part model was used to confirm the findings. Time to hospitalization was measured by the Kaplan-Meier survival formula. RESULTS: Compared to risperidone, olanzapine-treated patients had significantly lower hospitalization rates, (24.1% vs. 14.4%, respectively, p = 0.040) and significantly fewer hospitalization days (14.5 days vs. 9.9 days, respectively, p = 0.035). The mean difference of 4.6 days translated to $2,502 in annual psychiatric hospitalization cost savings per olanzapine-treated patient, on average. CONCLUSIONS: Consistent with prior clinical trial research, treatment-adherent schizophrenia patients who were treated in usual care with olanzapine had a lower risk of psychiatric hospitalization than risperidone-treated patients. Lower hospitalization costs appear to more than offset the higher medication acquisition cost of olanzapine

Integrating Randomized Placebo-Controlled Trial Data with External Controls: A Semiparametric Approach with Selective Borrowing

In recent years, real-world external controls (ECs) have grown in popularity as a tool to empower randomized placebo-controlled trials (RPCTs), particularly in rare diseases or cases where balanced randomization is unethical or impractical. However, as ECs are not always comparable to the RPCTs, direct borrowing ECs without scrutiny may heavily bias the treatment effect estimator. Our paper proposes a data-adaptive integrative framework capable of preventing unknown biases of ECs. The adaptive nature is achieved by dynamically sorting out a set of comparable ECs via bias penalization. Our proposed method can simultaneously achieve (a) the semiparametric efficiency bound when the ECs are comparable and (b) selective borrowing that mitigates the impact of the existence of incomparable ECs. Furthermore, we establish statistical guarantees, including consistency, asymptotic distribution, and inference, providing type-I error control and good power. Extensive simulations and two real-data applications show that the proposed method leads to improved performance over the RPCT-only estimator across various bias-generating scenarios

Medication adherence levels and differential use of mental-health services in the treatment of schizophrenia

<p>Abstract</p> <p>Background</p> <p>Adherence to antipsychotics for schizophrenia is associated with favorable clinical outcomes. This study compared annual mental-health service utilization by recent medication adherence levels for patients treated for schizophrenia, and assessed whether adherence levels change from pre- to post-psychiatric hospitalization.</p> <p>Methods</p> <p>We analyzed data from a large prospective, non-interventional study of patients treated for schizophrenia in the United States, conducted between 7/1997 and 9/2003. Detailed mental-health resource utilization was systematically abstracted from medical records and augmented with patients' self report. Medication possession ratio (MPR) with any antipsychotic in the 6 months prior to enrollment was used to categorize patients as: adherent (MPR ≥ 80%, N = 1758), partially adherent (MPR ≥ 60% < 80%, N = 36), or non-adherent (MPR < 60%, N = 216). Group comparisons employed propensity score-adjusted bootstrap re-sampling methods with 1000 iterations, adjusting for baseline patient demographic and clinical characteristics identified a priori.</p> <p>Results</p> <p>Adherent patients had a lower rate of psychiatric hospitalization compared with partially adherent and non-adherent patients (p < 0.001) and were more likely than non-adherent to engage in group therapy, individual therapy, and medication management. Most patients (92.0%) who were adherent in the 6 months prior to hospital admission continued to be adherent 6 months following hospitalization. However, 75.0% of previously partially adherent became adherent, and 38.7% of previously non-adherent became adherent following hospitalization.</p> <p>Conclusion</p> <p>Adherence is associated with lower utilization of acute care services and greater engagement in outpatient mental-health treatment. Adherence is a potentially dynamic phenomenon, which may improve, at least temporarily, following patients' psychiatric hospitalizations.</p

Involvement in the US criminal justice system and cost implications for persons treated for schizophrenia

<p>Abstract</p> <p>Background</p> <p>Individuals with schizophrenia may have a higher risk of encounters with the criminal justice system than the general population, but there are limited data on such encounters and their attendant costs. This study assessed the prevalence of encounters with the criminal justice system, encounter types, and the estimated cost attributable to these encounters in the one-year treatment of persons with schizophrenia.</p> <p>Methods</p> <p>This post-hoc analysis used data from a prospective one-year cost-effectiveness study of persons treated with antipsychotics for schizophrenia and related disorders in the United States. Criminal justice system involvement was assessed using the Schizophrenia Patients Outcome Research Team (PORT) client survey and the victimization subscale of the Lehman Quality of Life Interview (QOLI). Direct cost of criminal justice system involvement was estimated using previously reported costs per type of encounter. Patients with and without involvement were compared on baseline characteristics and direct annual health care and criminal justice system-related costs.</p> <p>Results</p> <p>Overall, 278 (46%) of 609 participants reported at least 1 criminal justice system encounter. They were more likely to be substance users and less adherent to antipsychotics compared to participants without involvement. The 2 most prevalent types of encounters were being a victim of a crime (67%) and being on parole or probation (26%). The mean annual per-patient cost of involvement was $1,429, translating to 6% of total annual direct health care costs for those with involvement (11% when excluding crime victims).</p> <p>Conclusions</p> <p>Criminal justice system involvement appears to be prevalent and costly for persons treated for schizophrenia in the United States. Findings highlight the need to better understand the interface between the mental health and the criminal justice systems and the related costs, in personal, societal, and economic terms.</p

A Bayesian approach to correct for unmeasured or semi-unmeasured confounding in survival data using multiple validation data sets

Purpose: The existence of unmeasured confounding can clearly undermine the validity of an observational study. Methods of conducting sensitivity analyses to evaluate the impact of unmeasured confounding are well established. However, application of such methods to survival data (“time-to-event” outcomes) have received little attention in the literature. The purpose of this study is to propose a novel Bayesian method to account for unmeasured confounding for survival data. &nbsp; Methods: The Bayesian method is proposed under an assumption that the supplementary information on unmeasured confounding in the form of internal validation data, external validation data or expert elicited prior distributions is available. The method for incorporating such information to Cox proportional hazard model is described.&nbsp; Simulation studies are performed based on the recently published instrumental variable method to assess the impact of unmeasured confounding and to illustrate the improvement of the proposed method over the naïve model which ignores unmeasured confounding. &nbsp; Results: Simulation studies illustrate the impact of ignoring the unmeasured confounding and the effectiveness of our Bayesian approach. The corrected model had significantly less bias and coverage of 95% intervals much closer to nominal. &nbsp; Conclusion: The proposed Bayesian method provides a useful and flexible tool in incorporating different types of supplemental information on unmeasured confounding to adjust the treatment estimates when the outcome is survival data.&nbsp; It out-performed the naïve model in simulation studies based on a real world study. &nbsp