Cost per Patient Achieving Treatment Targets and Number Needed to Treat with Tirzepatide Versus Semaglutide 1 mg in Patients with Type 2 Diabetes in the United States.

INTRODUCTION: Achieving glycemic control can help reduce complications of type 2 diabetes (T2D). This study compared the pharmacy cost per responder and number needed to treat (NNT) of tirzepatide 5 mg, 10 mg, and 15 mg versus semaglutide 1 mg to achieve glycemic, weight loss, and composite treatment endpoints in patients with T2D in the United States. METHODS: The proportions of patients achieving glycemic, weight loss, and composite treatment endpoints were obtained from the phase 3 SURPASS-2 randomized clinical trial which compared tirzepatide 5 mg, 10 mg, and 15 mg to semaglutide 1 mg. Annual pharmacy costs were calculated using 2022 wholesale acquisition costs. Cost per responder and NNT were calculated along with 95% confidence intervals and tests for statistical significance (P ≤ 0.05). RESULTS: Tirzepatide had a lower cost per responder to achieve glycated hemoglobin A1c (HbA1c) endpoints of ≤ 6.5% (10 mg and 15 mg doses) and < 5.7% (all doses) and weight loss endpoints of ≥ 5% (10 mg and 15 mg doses), ≥ 10% (all doses), and ≥ 15% (all doses). The cost per responder to achieve HbA1c < 7% (all doses of tirzepatide) and ≤ 6.5% (5 mg tirzepatide) were not statistically significantly different between tirzepatide and semaglutide 1 mg. The cost per patient to achieve the composite endpoints (HbA1c < 7.0%, ≤ 6.5%, or < 5.7%/weight loss ≥ 10%/no hypoglycemia) was statistically significantly lower for all doses of tirzepatide than for semaglutide 1 mg. The NNTs for all doses of tirzepatide were statistically significantly lower than that for semaglutide 1 mg to achieve all individual and composite endpoints, with the exception of the 5 mg dose for HbA1c < 7.0% and HbA1c ≤ 6.5%, where tirzepatide had numerically lower NNTs that were not statistically significant. CONCLUSION: Tirzepatide is a novel glucose-dependent insulinotropic polypeptide (GIP) and glucagon-like peptide-1 (GLP-1) receptor agonist (RA) that may offer the potential to achieve stringent glycemic goals, weight loss targets, and composite treatment goals at a lower cost per responder compared to semaglutide 1 mg among people with T2D.

A gene expression signature predicts recurrence-free survival in meningioma.

BACKGROUND: Meningioma is the most common primary brain tumor and has a variable risk of local recurrence. While World Health Organization (WHO) grade generally correlates with recurrence, there is substantial within-grade variation of recurrence risk. Current risk stratification does not accurately predict which patients are likely to benefit from adjuvant radiation therapy (RT). We hypothesized that tumors at risk for recurrence have unique gene expression profiles (GEP) that could better select patients for adjuvant RT. METHODS: We developed a recurrence predictor by machine learning modeling using a training/validation approach. RESULTS: Three publicly available AffymetrixU133 gene expression datasets (GSE9438, GSE16581, GSE43290) combining 127 primary, non-treated meningiomas of all grades served as the training set. Unsupervised variable selection was used to identify an 18-gene GEP model (18-GEP) that separated recurrences. This model was validated on 62 primary, non-treated cases with similar grade and clinical variable distribution as the training set. When applied to the validation set, 18-GEP separated recurrences with a misclassification error rate of 0.25 (log-rank p=0.0003). 18-GEP was predictive for tumor recurrence [p=0.0008, HR=4.61, 95%CI=1.89-11.23)] and was predictive after adjustment for WHO grade, mitotic index, sex, tumor location, and Simpson grade [p=0.0311, HR=9.28, 95%CI=(1.22-70.29)]. The expression signature included genes encoding proteins involved in normal embryonic development, cell proliferation, tumor growth and invasion (FGF9, SEMA3C, EDNRA), angiogenesis (angiopoietin-2), cell cycle regulation (CDKN1A), membrane signaling (tetraspanin-7, caveolin-2), WNT-pathway inhibitors (DKK3), complement system (C1QA) and neurotransmitter regulation (SLC1A3, Secretogranin-II). CONCLUSIONS: 18-GEP accurately stratifies patients with meningioma by recurrence risk having the potential to guide the use of adjuvant RT.

Impact of constipation on opioid therapy management among long-term opioid users, based on a patient survey.

OBJECTIVE: The authors sought to characterize health-related quality of life (HRQoL), medication adherence, productivity losses, and treatment satisfaction associated with modifications to opioid therapy due to opioid-induced constipation (OIC). DESIGN: A cross-sectional, between-subjects design was used to examine health outcomes among US noncancer participants currently taking opioids. PATIENTS, PARTICIPANTS: Participants were adults in the 2012 US National Health and Wellness Survey, who reported currently using opioids (> 30 days) and experiencing constipation. Respondents were categorized as making modifications to opioid therapy due to OIC (modifiers, n = 244) or making no modifications (nonmodifiers, n = 247). MAIN OUTCOME MEASURES: Patient Assessment of Constipation Quality of Life (PAC-QoL) and Symptoms (PAC-Sym), Morisky Medication Adherence Scale (MMAS-4), Work Productivity and Activity Impairment, and the Treatment Satisfaction Questionnaire for Medication (TSQM II) for OIC treatment were administered. Generalized linear models were adjusted to control for baseline characteristics (age, gender, comorbidities, opioid strength, etc). RESULTS: Modifiers reported poorer HRQoL (PAC-QoL total: 1.74 vs 1.44, p < 0.001), worse constipation (PAC-Sym total: 1.56 vs 1.35, p = 0.003), more pain-related resource use (surgery: odds ratio (OR) = 3.72, p = 0.002; emergency room visits: OR = 1.88, p = 0.049; hospitalizations: OR = 2.47, p = 0.033), and lower adherence (MMAS-4 pain: OR = 0.12, p < 0.001; MMAS-4 OIC: OR = 0.39, p < 0.001) than nonmodifiers. Modifiers reported greater presenteeism (49.75 percent vs 38.28 percent, p = 0.038), but no significant differences were found for activity impairment or OIC treatment satisfaction. CONCLUSIONS: Treating OIC effectively may help prevent inadequate pain management secondary to opioid therapy modification, help increase HRQoL, lessen OIC symptoms, decrease productivity loss, and improve adherence to opioid and OIC treatments.

Diffusion MR Characteristics Following Concurrent Radiochemotherapy Predicts Progression-Free and Overall Survival in Newly Diagnosed Glioblastoma.

The standard of care for newly diagnosed glioblastoma (GBM) is surgery, then radiotherapy (RT) with concurrent temozolomide (TMZ), followed by adjuvant TMZ. We hypothesized patients with low diffusivity measured using apparent diffusion coefficient (ADC) histogram analysis evaluated after RT+TMZ, prior to adjuvant TMZ, would have a significantly shorter progression-free (PFS) and overall survival (OS). To test this hypothesis we evaluated 120 patients with newly diagnosed GBM receiving RT+TMZ followed by adjuvant TMZ. MRI was performed after completion of RT+TMZ, prior to initiation of adjuvant TMZ. A double Gaussian mixed model was used to describe the ADC histograms within the enhancing tumor, where ADCL and ADCH were defined as the mean ADC value of the lower and higher Gaussian distribution, respectively. An ADCL value of 1.0 um2/ms and ADCH value of 1.6 um2/ms were used to stratify patients into high and low risk categories. Results suggest patients with low ADCL had significantly shorter PFS (Cox Hazard Ratio = 0.12, P = 0.0006). OS was significantly shorter with low ADCL tumors, showing a median OS of 407 vs. 644 days (Cox Hazard Ratio = 0.31, P = 0.047). ADCH was not predictive of PFS or OS when accounting for age and ADCL. In summary, newly diagnosed glioblastoma patients with low ADCL after completion of RT+TMZ are likely to progress and die earlier than patients with higher ADCL. Results suggest ADC histogram analysis may be useful for patient risk stratification following completion of RT+TMZ.

Tumor-suppressive miR148a is silenced by CpG island hypermethylation in IDH1-mutant gliomas.

PURPOSE: IDH1/2-mutant gliomas harbor a distinct glioma-CpG island methylation phenotype (G-CIMP) that may promote the initiation and progression of secondary pathway gliomas by silencing tumor-suppressive genes. The potential role of tumor-suppressive microRNAs (miRNA; miR) in this process is not understood. EXPERIMENTAL DESIGN: To identify potential tumor-suppressive miRNA hypermethylated in glioma, the methylation profiles of IDH1/2(WT) gliomas (n = 11) and IDH1(MUT) glioma (n = 20) were compared by using massively parallel reduced representation bisulfite sequencing (RRBS). The methylation status of selected miRNA was validated by using targeted bisulfite sequencing (BiSEQ) in a large cohort of glioma tissue samples including 219 IDH1(WT) and 72 IDH1/2(MUT) samples. The expression of selected miRNAs was determined by using the TaqMan qPCR. Functional analyses of miR148a were conducted and target genes were identified. RESULTS: We identify miR148a as a novel, G-CIMP-associated miRNA whose methylation is tightly correlated with IDH1 mutation and associated with improved survival in patients with malignant glioma. We confirm that downregulation of miR148a can occur via DNA methylation. We demonstrate that IDH1 mutation provides a mechanism of miR148a methylation and downregulation, and that restoration of miR148a reduced tumorigenic properties of glioma cells, possibly by targeting DNMT1. CONCLUSIONS: We identify miR148a as a novel G-CIMP-associated miRNA, and provide results suggesting that miR148a restoration may have therapeutic implications.

Deferred use of bevacizumab for recurrent glioblastoma is not associated with diminished efficacy.

BACKGROUND: The optimal timing to initiate bevacizumab (BV) therapy for recurrent glioblastoma (GBM) is currently unclear. To address this issue, we examined progression-free survival (PFS) and survival time (ST) in a large retrospective cohort of GBM patients treated with BV at different recurrences. METHODS: We identified 468 primary GBM patients who underwent biopsy or surgery followed by radiation therapy and temozolomide (RT/TMZ), and then received BV. PFS and ST were compared between patients stratified by the recurrence that BV was initiated (upfront, first recurrence, second recurrence, or 3+ recurrences). We also examined the effect on PFS and ST of the addition of chemotherapy to BV. In a larger cohort of GBM patients, we determined overall treatment continuation rates at each recurrence and identified variables predictive of inability to continue treatment. RESULTS: BV PFS was similar for all 3 recurrence groups (median, 4.1 months). There were no differences in BV ST (median, 9.8 months). The addition of chemotherapy to BV improved PFS but not ST. Analysis of treatment continuation rates indicated that the number of patients unable to undergo further treatments is modest, and that patients unable to tolerate BV delay can be identified by age ≥60 years and low extent of resection. CONCLUSIONS: Deferred use of bevacizumab is not associated with diminished efficacy. Analysis of treatment continuation rates identified patients who may be unable to delay BV therapy. Our findings suggest that there is a fixed survival after BV initiation and that delayed BV treatment is preferable for most patients.

Identification of retinol binding protein 1 promoter hypermethylation in isocitrate dehydrogenase 1 and 2 mutant gliomas.

BACKGROUND: Mutations in isocitrate dehydrogenase 1 (IDH1) and associated CpG island hypermethylation represent early events in the development of low-grade gliomas and secondary glioblastomas. To identify candidate tumor suppressor genes whose promoter methylation may contribute to gliomagenesis, we compared methylation profiles of IDH1 mutant (MUT) and IDH1 wild-type (WT) tumors using massively parallel reduced representation bisulfite sequencing. METHODS: Reduced representation bisulfite sequencing was performed on ten pathologically matched WT and MUT glioma samples and compared with data from a methylation-sensitive restriction enzyme technique and data from The Cancer Genome Atlas (TCGA). Methylation in the gene retinol-binding protein 1 (RBP1) was identified in IDH1 mutant tumors and further analyzed with primer-based bisulfite sequencing. Correlation between IDH1/IDH2 mutation status and RBP1 methylation was evaluated with Spearman correlation. Survival data were collected retrospectively and analyzed with Kaplan-Meier and Cox proportional hazards analysis. All statistical tests were two-sided. RESULTS: Methylome analysis identified coordinated CpG island hypermethylation in IDH1 MUT gliomas, consistent with previous reports. RBP1, important in retinoic acid metabolism, was found to be hypermethylated in 76 of 79 IDH1 MUT, 3 of 3 IDH2 MUT, and 0 of 116 IDH1/IDH2 WT tumors. IDH1/IDH2 mutation was highly correlated with RBP1 hypermethylation (n = 198; Spearman R = 0.94, 95% confidence interval = 0.92 to 0.95, P < .001). The Cancer Genome Atlas showed IDH1 MUT tumors (n = 23) to be RBP1-hypermethylated with decreased RBP1 expression compared with WT tumors (n = 124). Among patients with primary glioblastoma, patients with RBP1-unmethylated tumors (n = 102) had decreased median overall survival compared with patients with RBP1-methylated tumors (n = 22) (20.3 months vs 36.8 months, respectively; hazard ratio of death = 2.48, 95% confidence interval = 1.30 to 4.75, P = .006). CONCLUSION: RBP1 promoter hypermethylation is found in nearly all IDH1 and IDH2 mutant gliomas and is associated with improved patient survival. Because RBP1 is involved in retinoic acid synthesis, our results suggest that dysregulation of retinoic acid metabolism may contribute to glioma formation along the IDH1/IDH2-mutant pathway.

Impact of noncompliance with urate-lowering drug on serum urate and gout-related healthcare costs: administrative claims analysis.

OBJECTIVE: To determine the association between allopurinol compliance and serum urate (sUA) level; and examine the association between sUA and gout-related healthcare costs in a large managed care population. RESEARCH DESIGN AND METHODS: This retrospective administrative claims analysis examined subjects with gout (> or = 2 medical claims with ICD-9-CM diagnosis code 274.xx or > or = 1 claim with a gout diagnosis and > or = 1 pharmacy claim for allopurinol, probenecid, colchicine, or sulfinpyrazone) between January 1, 2002 and March 31, 2004. Each subject was observed during 1-year pre-index and 1-year post-index periods. MAIN OUTCOME MEASURES: Outcomes were allopurinol medication possession ratio (MPR) and compliance (MPR > or = 0.80), sUA (mg/dL), and gout-related healthcare costs. 'Post-allopurinol' sUA was measured during three periods after the first observed allopurinol fill: 30-89 days; 90-149 days; > or = 150 days. A baseline sUA on or before the start of the post-index period was also identified. Outcomes were stratified by post-allopurinol or baseline sUA and compliance. Generalized linear modeling (GLM) regression measured the impact of baseline sUA on gout-related healthcare costs, controlling for demographic and health status variables. RESULTS: The study sample comprised 18,243 subjects with mean age of 53.9 years. In all, 55% (n = 10,073) of subjects used allopurinol. There were 1473 (8.1%) subjects with a post-allopurinol sUA and 2438 (13.4%) subjects with a baseline sUA result. Among all subjects with a post-allopurinol sUA, 45.6% were compliant; between 49.3% and 56.8% of compliant subjects had an sUA < 6.0 mg/dL compared with 22.5-27.8% of non-compliant subjects, depending on the post-allopurinol time period (all p < 0.001). GLM results showed gout-related costs associated with baseline sUA > or = 6.0 and < 9.0 mg/dL were 58% higher (95% confidence interval (CI): 1.012 -2.456; p = 0.044) than were costs for sUA < 6.0 mg/dL. There was no significant difference in gout-related costs between baseline sUA < 6.0 mg/dL and > or = 9.0 mg/dL. CONCLUSIONS: Analysis revealed an important associations between allopurinol compliance, sUA, and gout-related costs: compliance was positively associated with favorable sUA (<6.0 mg/dL) in unadjusted comparisons. GLM showed that baseline sUA < 6.0 was inversely associated with gout-related costs relative to baseline sUA > or = 6.0 and <9.0 mg/dL. Nevertheless, a substantial portion of subjects, even compliant ones, did not achieve sUA < 6.0 mg/dL. These results should be interpreted carefully in light of study limitations, including incomplete laboratory data, the potentially incorrect inference that medications were taken as prescribed, and lack of generalizability from Medicare managed care enrollees to the broader Medicare population.

Cumulative cost pattern comparison of prostate cancer treatments.

BACKGROUND: Studies that compare prostate cancer treatment costs show wide variation. None compare all contemporary treatment costs, and most focus on initial treatment costs. The authors compared healthcare utilization and cost patterns of prostate cancer treatments over a span of 5.5 years in 4553 newly diagnosed patients stratified by age and risk group. METHODS: Contemporary treatment and evaluation patterns for prostate cancer were identified by using CaPSURE, a national disease registry of men with prostate cancer that included ongoing clinical data collection from 31 academic and community urology practices and biennial patient-reported outcome questionnaires that included demography, medical condition, comorbidity, risk measures, and healthcare utilization. Costs of outpatient visits, medications, and hospitalizations were applied from various national sources. Recurrent events analysis (MCF) accounted for left and right censorship. A mixed effects regression model with bootstrapping for skewed cost data quantified the relation between MCF cost, age, and risk. RESULTS: Prostate-related costs in the first 6 months after treatment were 11,495 dollars, (from 2586 dollars for watchful waiting (WW) to 24,204 dollars for external beam radiation. After 6 months, average cost was only 3044 dollars. Annual cost is 7740 dollars, highest for androgen deprivation therapy (12,590 dollars) and lowest for watch waiting (5843 dollars). Risk and age were significantly related to initial treatment choice. Cumulative cost (42,570 dollars) allowed a better estimate of treatment pattern costs. CONCLUSIONS: The cost burden of prostate cancer is high, but it varies by treatment type even when controlling for disease, age, and stage. Cumulative cost analysis allowed inclusion of adverse events and disease recurrence costs, making new cost comparisons evident among treatments.

Smoking status and health-related quality of life: as findings from the 2001 Behavioral Risk Factor Surveillance System data.

PURPOSE: To examine the relationship between smoking status and health-related quality of life (HRQOL). DESIGN: Our study used a cross-sectional analysis with self-reported data from the 2001 Behavioral Risk Factor Surveillance System (BRFSS). SETTING: United States. SUBJECTS: Subjects were a representative sample of noninstitutionalized adults aged 18 years and older. After excluding respondents who reported being pregnant and for whom smoking status could not be determined, we included 209,031 respondents. MEASURES: Multiple logistic regressions were performed to examine the associations of smoking status with the four HRQOL items, controlling for demographic and health-related characteristics. RESULTS: Current smokers had a higher likelihood of reporting poor general health status compared with nonsmokers and ex-smokers. Compared with nonsmokers, current smokers had a higher likelihood of reporting > or = 14 days of poor physical health (odds ratio [OR] = 1.64, 95% confidence interval [CI] = 1.51-1.77), poor mental health (OR = 1.99, 95% Cl = 1.84-2.16), and activity limitations (OR = 1.80, 95% Cl = 1.63-2.00). Similarly, compared with ex-smokers, current smokers had a higher likelihood of reporting > or = 14 days of poor physical health (OR = 1.30, 95% CI = 1.19-1.42), poor mental health (OR = 1.65, 95% CI = 1.50-1.81), and activity limitations (OR = 1.48, 95% CI = 1.32-1.65). Age, income, and presence of comorbidities also significantly explained variation in HRQOL. CONCLUSIONS: Our study reaffirms the significant association between smoking and HRQOL in a large nationally representative sample. Poor health associated with smoking persists as a major public health problem, and effective preventive and smoking cessation efforts should be undertaken.