Examining the heterogeneity of treatment patterns in attention deficit hyperactivity disorder among children and adolescents in the Texas Medicaid population: modeling suboptimal treatment response.

Objectives: To examine suboptimal responses (SR) in attention deficit hyperactivity disorder (ADHD) among pediatric patients in the Texas Medicaid program receiving osmotic-release oral system methylphenidate (OROS-MPH) or lisdexamfetamine (LDX) and apply an SR prediction model to identify patients most likely to experience an SR to either OROS-MPH or LDX therapies. Methods: A retrospective cohort study was conducted using Texas Medicaid claims data of ADHD children and adolescents (6-17 years of age) initiating OROS-MPH or LDX. Primary SR endpoints were drug discontinuation, switching, and augmentation 12-months post-ADHD drug initiation. Logistic regression models were developed to predict SR to OROS-MPH and LDX in 1:1 matched groups of children and adolescent cohorts. Results: A total of 3,633 children and 1,611 adolescents were matched for each cohort. SR was observed among more children (76.4% vs 72.3%; p < 0.001) and adolescents (82.7% vs 78.2%; p = 0.002) initiating OROS-MPH compared to LDX. Patient sub-groups with the highest predicted risk of OROS-MPH SR experienced significantly lower observed SR rates (p < 0.05) when initiating LDX (children: 80.6% for OROS-MPH vs 75.8% for LDX; OR = 0.75, 95% CI = 0.60-0.94; adolescents: 87.2% for OROS-MPH vs 80.6% for LDX; OR = 0.61, 95% CI = 0.41-0.89). For patients with highest predicted SR rates to LDX, observed SR rates were not significantly different between patients initiating LDX or OROS-MPH. Conclusions: This study demonstrated how a personalized medicine approach using administrative claims data can be used to identify sub-groups of child and adolescent ADHD patients with different risks for suboptimal response with OROS-MPH or LDX in a Medicaid population.

Impact of mental health comorbidities on health care utilization and expenditure in a large US managed care adult population with ADHD.

OBJECTIVE: To estimate the health resource use (HRU) and expenditure of adult patients with attention deficit/hyperactivity disorder (ADHD) subsequently diagnosed with one or more mental health (MH) comorbidities. METHODS: Using Kaiser Permanente Southern California electronic medical records (January 1, 2006, to December 31, 2009), we identified adults with at least one ADHD diagnosis and at least two subsequent prescriptions fills for ADHD medication. The date of first MH comorbidity diagnosis after the index ADHD diagnosis was defined as the index transition date. Continuous eligibility 12 months before and after the index transition date was required. For patients with multiple transitions (≥2), the post-transition period reflected the 12 months after the second transition. HRU for all-cause inpatient, outpatient, emergency department, behavioral therapy, overall prescription fill counts, and ADHD-specific prescription fill counts and mean patient expenditure (2010 US $) were estimated. Generalized estimating equations were used to evaluate differences in HRU and expenditure between the pre- and post-transition periods, respectively. RESULTS: Of the 3809 patients with ADHD identified, 989 (26%) had at least one transition (n = 357 single and n = 632 multiple). From the pre- to the post-transition period, for single transition cohort, all HRU increased significantly except for behavioral therapy. In the multiple transition cohort, all HRU increased significantly. Total expenditure increased by mean ± SE of $1822 ± $306 and $4432 ± $301 (both P < 0.0001) in the single and multiple transition cohorts, respectively. CONCLUSIONS: Twenty-six percent of patients with ADHD transitioned to MH comorbid diagnoses. Increased HRU and expenditure were associated with MH transitions. Identifying of patients with ADHD at risk for MH comorbidities may help to improve their outcomes.

Cost effectiveness of guanfacine extended release as an adjunctive therapy to a stimulant compared with stimulant monotherapy for the treatment of attention-deficit hyperactivity disorder in children and adolescents.

BACKGROUND: Attention-deficit hyperactivity disorder (ADHD) is a common psychiatric disorder in childhood, affecting 3-7% of school-age children in the US and imposing substantial economic burden. Stimulants are considered first-line pharmacological treatment and are the most prescribed treatment for ADHD. However, approximately 30% of children with ADHD do not have an optimal response to a single stimulant and may require adjunctive therapy. OBJECTIVE: Our objective was to conduct a cost-effectiveness analysis (CEA) of adding a non-stimulant, guanfacine extended release (GXR), to stimulants versus maintaining existing stimulant monotherapy in the treatment of ADHD in children and adolescents with suboptimal response to stimulant monotherapy. METHODS: A 1-year Markov model was developed to estimate costs and effectiveness from a US third-party payer perspective. Effectiveness was measured by the QALY. The model assumed that patients transitioned among four health states (normal, mild, moderate and severe), defined by the Clinical Global Impression-Severity (CGI-S) scale. Transition probabilities were estimated in an ordered logit model using patient-level data from a multicentre, 9-week, double-blind, placebo-controlled, dose-optimization study, where subjects (n = 461) continued their stable morning stimulant and were randomized to GXR administered in the morning, GXR administered in the evening, or placebo. The model assumed that patients in moderate/severe health states after week 8 would discontinue ADHD treatment and remain in that state for the rest of the study period. Direct costs included drug wholesale acquisition costs and health state costs, all in $US, year 2010 values. Utility associated with each health state was obtained from the literature and disutilities associated with adverse events were applied for the first 4 weeks. One-way sensitivity analyses and probabilistic sensitivity analysis (PSA) were conducted by varying costs, utilities, adverse-event duration, and transition probabilities. RESULTS: Compared with maintaining existing stimulant monotherapy, adding GXR to existing stimulant monotherapy was associated with an incremental drug cost of $US1016 but a lower medical cost of $US124, resulting in a total incremental cost of $US892 at 1 year. The addition of GXR to stimulants led to an incremental QALY of 0.03 and an incremental cost-effectiveness ratio (ICER) of $US31,660/QALY. In one-way sensitivity analysis, ICER values ranged from $US19,723, when 100% of patients were assumed to be severe in their initial health state, to $US46,631, when the last observed states from the clinical trial were carried forward to the end of the 1-year analysis period. PSA demonstrated a 94.6% likelihood that the ICER falls below $US50,000/QALY. CONCLUSIONS: The impairment associated with residual ADHD symptoms after stimulant therapy is becoming increasingly recognized. This is the first analysis of the cost effectiveness of stimulants combined with an adjunctive medication. This study suggests that the adjunctive therapy of GXR with stimulants is a cost-effective treatment based on a willingness-to-pay threshold of $US50,000/QALY. This may address an unmet need among patients with suboptimal response to stimulant monotherapy.

Economic consequence of switching to citalopram after its generic entry for adult patients with major depressive disorder (MDD) treated with escitalopram: a 6-month retrospective study.

OBJECTIVE: To estimate, from a third-party payer's perspective, the effects of switching from escitalopram to citalopram, after the generic entry of citalopram, on hospitalization and healthcare costs among adult MDD patients who were on escitalopram therapy. METHODS: Adult MDD patients treated with escitalopram were identified from Ingenix Impact claims database. MDD- and mental health (MH)-related hospitalization rates and healthcare costs were compared between 'switchers' (patients who switched to citalopram after its generic entry) and 'non-switchers'. MDD- and MH-related outcomes were defined as having a primary or a secondary diagnosis of ICD-9-CM = 296.2x, 296.3x and ICD-9-CM = 290-319, respectively. A propensity score matching method that estimated the likelihood of switching using baseline characteristics was used. Outcomes were examined for both 3-month and 6-month post-index periods. RESULTS: The sample included 3,427 matched pairs with balanced baseline characteristics. Switchers were more likely to incur an MDD-related (odds ratio [OR] = 1.52) and MH-related hospitalization (OR = 1.34) during the 6-month post-index period (both p < 0.05). Compared to switchers, non-switchers had significantly lower MDD- and MH-related hospitalization costs ($248.3 and $219.8 lower, respectively) and medical costs ($277.4 and $246.4 lower, respectively) (all p < 0.05). Although non-switchers had significantly higher MDD- and MH-related prescription drug costs, overall they had significantly lower total MDD- and MH-related healthcare costs ($109.9 and $93.6 lower, respectively; both p < 0.001). The 3-month results were consistent with these 6-month findings. LIMITATIONS: The study limitations included limited generalizability of study findings, inability to differentiate switching from escitalopram to citalopram due to medical reasons versus non-medical reasons, and exclusion of indirect costs from cost calculations. CONCLUSIONS: Compared to patients maintaining on escitalopram, switchers from escitalopram to citalopram experienced higher risk of MDD- and MH-related hospitalization and incurred higher total MDD- and MH-related healthcare costs. The economic consequences of therapeutic substitution should take into account total healthcare costs, not just drug acquisition costs.

Healthcare utilization and costs incurred by patients with major depression after being switched from escitalopram to another SSRI for non-medical reasons.

OBJECTIVE: To compare healthcare utilization and costs for major depressive disorder (MDD) patients treated with escitalopram and who were switched to another SSRI for non-medical reasons versus those who did not switch. RESEARCH DESIGN AND METHODS: Patients were identified in the Ingenix Impact Database (2003-2006). The analysis group included patients who remained on escitalopram for ≥ 90 days and switched to another SSRI within 45 days of end of supply days for non-medical reasons; the control group included matched individuals who did not switch within 45 days. Switching for medical reasons was defined as switching within 7 days after having a hospitalization, an emergency room (ER) visit, or a psychotherapy visit. Outcomes (all-cause and MDD-related) were analyzed over 3 months and included use of hospital, ER, outpatient visits and professional services, and healthcare costs. Outcomes were compared between the two groups using descriptive statistics and regression analyses controlling for differences in baseline characteristics. Costs were inflation adjusted to 2006 US dollars. RESULTS: The study included 2,805 matched pairs. Compared to controls, switchers had higher rates of all-cause and MDD-related hospitalizations (relative risk [RR] = 1.4 and 2.0, respectively) and all-cause and MDD-related ER visits (RR = 1.2 and 1.6, respectively, all p ≤ 0.05). Results from multivariate analyses show that switchers had higher medical costs (+$138), drug costs (+$149) and total healthcare costs (+$322) compared to patients in the control group (all p < 0.0001). LIMITATIONS: This study's limitations include its short observational period and definition of switching for non-medical reasons. CONCLUSION: Patients who were switched to another SSRI for non-medical reasons after being stabilized on escitalopram used more resources and had higher healthcare costs within 3 months of switching than patients who did not switch.

Escitalopram versus sertraline in the treatment of major depressive disorder: a randomized clinical trial.

OBJECTIVE: This trial was conducted to compare the efficacy and tolerability of a fixed dose of escitalopram 10 mg/day with sertraline optimally dosed within its recommended dose range (50-200 mg/day) for the treatment of major depressive disorder. METHODS: In this multicenter trial, depressed patients (DSM-IV defined; baseline Montgomery-Asberg Depression Rating Scale [MADRS] 22) aged 18-80 years were randomly assigned to 8 weeks of double-blind treatment with escitalopram (10 mg/day) or sertraline (50-200 mg/day) following a 1-week single-blind placebo lead-in period. There was no placebo comparison arm. Sertraline was initiated at 50 mg/day, and could be increased by 50 mg/day at weekly intervals based on clinical need and tolerability at the lower dose level. The blind was maintained with matching double-blind placebo capsules for the escitalopram group. Change from baseline to endpoint in MADRS total score (last observation carried forward) was the primary efficacy measure. RESULTS: A total of 212 patients received double-blind medication. At week 8, the mean sertraline dosage was 144 mg/day (median = 150 mg/day). Mean changes from baseline to endpoint in MADRS scores were -19.1 and -18.4 for the escitalopram and sertraline groups, respectively. At endpoint, 75% and 70% of escitalopram- and sertraline-treated patients, respectively, were responders (> or =50% improvement from baseline in mean MADRS scores). Both treatments were generally well tolerated; only 2% and 4% of patients prematurely discontinued escitalopram and sertraline treatment, respectively, due to adverse events. CONCLUSION: No differences in efficacy were observed for fixed-dose escitalopram 10 mg/day and sertraline flexibly dosed from 50-200 mg/day. At these doses, both escitalopram and sertraline were generally well tolerated.

Cost-utility comparison of escitalopram and sertraline in the treatment of major depressive disorder.

OBJECTIVE: To construct a cost-utility model comparing escitalopram with sertraline in the treatment of major depressive disorders. METHODS: A decision analytic model was created to compare the cost-utility of these two antidepressants from the perspective of a managed-care organization. The model was designed to compare 10-20 mg/day of escitalopram to 50-200 mg/day of sertraline. Benefits (utility) scores were calculated based on clinical and utility data obtained from the literature. Direct medical costs included costs of the antidepressants, titration, treatment failures, and adverse events. Costs and benefits were modeled for a 6-month period and the model was subjected to thorough sensitivity analyses. RESULTS: The estimated 6-month total cost was 919 dollars for escitalopram and 1351 dollars for sertraline. The estimated QALYs were 0.40296 for escitalopram and 0.39268 for sertraline. These differences were mostly due to differences in drug acquisition costs and adverse events. The robustness of the cost-utility model results were tested in a Monte Carlo simulation of 10 000 patients and it indicated an 88.5% probability that escitalopram was the dominant therapy, suggesting both lower costs and greater QALYs. CONCLUSION: This cost-utility model that incorporated the costs of titration and impact of side-effects comparing escitalopram 10-20 mg per day and sertraline 50-200 mg per day shows that escitalopram appeared to be less costly and produced efficacy (utility) at least as good as and maybe slightly better than that of sertraline.

First-cycle absolute neutrophil count can be used to improve chemotherapy-dose delivery and reduce the risk of febrile neutropenia in patients receiving adjuvant therapy: a validation study.

BACKGROUND: The nadir value of the absolute neutrophil count (ANC) in the first cycle of chemotherapy is an effective predictor of subsequent neutropenic events. This study was designed to validate an earlier published study based on a retrospective data analysis from a prospective randomized clinical trial. METHODS: The original published model was applied to a trial of 143 patients to cross-validate the model. We also tested the specification of the model on our data by using a logistic regression model with several variables, including first-cycle nadir ANC, age, menopausal status, hormone-receptor status, previous radiotherapy, and first-cycle decrease in hemoglobin concentration. Patients received fluorouracil, doxorubicin, and cyclophosphamide every 21 or 28 days for six cycles without hematopoietic support from colony-stimulating factor. RESULTS: In the cross-validation analysis, the original model successfully classified patients by risk of neutropenic events (C = 0.78). When the model specification was tested, first-cycle nadir ANC was the sole significant (P < 0.0001) predictor of neutropenic events and the model had a good predictive power (C = 0.78). The estimated relative risk of 4.8 did not differ from the risk cited in the original model (P = 0.91). A significantly higher percentage of our patients with a low first-cycle nadir ANC of 0.25 x 10(9)/liter or less experienced febrile neutropenia (30% versus 10%, P = 0.04) and received at least 85% of the planned dose intensity (55% versus 32%, P = 0.05). CONCLUSIONS: The original risk model used to predict neutropenic events was validated by our study. This information can be used to target high-risk patients for prophylactic treatment with filgrastim (recombinant methionyl human granulocyte colony-stimulating factor) in chemotherapy cycles 2 to 6.