IMPORTANCE In response to the increase in opioid overdose deaths in the United States, many states recently have implemented supply-controlling and harm-reduction policy measures. To date, an updated policy evaluation that considers the full policy landscape has not been conducted. OBJECTIVE To evaluate 6 US state-level drug policies to ascertain whether they are associated with a reduction in indicators of prescription opioid abuse, the prevalence of opioid use disorder and overdose, the prescription of medication-assisted treatment (MAT), and drug overdose deaths. DESIGN, SETTING, AND PARTICIPANTS This cross-sectional study used drug overdose mortality data from 50 states obtained from the National Vital Statistics System and claims data from 23 million commercially insured patients in the US between 2007 and 2018. Difference-indifferences analysis using panel matching was conducted to evaluate the prevalence of indicators of prescription opioid abuse, opioid use disorder and overdose diagnosis, the prescription of MAT, and drug overdose deaths before and after implementation of 6 state-level policies targeting the opioid epidemic. A random-effects meta-analysis model was used to summarize associations over time for each policy and outcome pair. The data analysis was conducted July 12, 2020. EXPOSURES State-level drug policy changes to address the increase of opioid-related overdose deaths included prescription drug monitoring program (PDMP) access, mandatory PDMPs, pain clinic laws, prescription limit laws, naloxone access laws, and Good Samaritan laws. MAIN OUTCOMES AND MEASURES The outcomes of interests were quarterly state-level mortality from drug overdoses, known indicators for prescription opioid abuse and doctor shopping, MAT, and prevalence of drug overdose and opioid use disorder. RESULTS This cross-sectional study of drug overdose mortality data and insurance claims data from 23 million commercially insured patients (12 582 378 female patients [55.1%]; mean [SD] age, 45.9 [19.9] years) in the US between 2007 and 2018 found that mandatory PDMPs were associated with decreases in the proportion of patients taking opioids (−0.729%; 95% CI, −1.011% to −0.447%), with overlapping opioid claims (−0.027%; 95% CI, −0.038% to −0.017%), with daily morphine milligram equivalent greater than 90 (−0.095%; 95% CI, −0.150% to −0.041%), and who engaged in drug seeking (−0.002%; 95% CI, −0.003% to −0.001%). The proportion of patients receiving MAT increased after the enactment of mandatory PDMPs (0.015%; 95% CI, 0.002% to 0.028%), pain clinic laws (0.013%, 95% CI, 0.005%-0.021%), and prescription limit laws (0.034%, 95% CI, 0.020% to 0.049%). Mandatory PDMPs were associated with a decrease in the number of overdose deaths due to natural opioids (−518.5 [95% CI, −728.5 to −308.5] per 300 million people) and methadone (−122.7 [95% CI, −207.5 to −37.8] per 300 million people). Prescription drug monitoring program access policies showed similar results, although these policies were also associated with increases in overdos...

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Parsaclisib, a potent, highly selective, next-generation PI3Kd inhibitor, was evaluated as monotherapy in CITADEL-202 (NCT02998476), an open-label, multicenter, phase 2 study in patients with relapsed or refractory diffuse large B-cell lymphoma. Patients enrolled into 2 groups (A, Bruton tyrosine kinase [BTK] inhibitor naïve, n ¼ 55; B, BTK inhibitor experienced, n ¼ 5) received oral parsaclisib 20 mg once daily for 8 weeks, then 20 mg once weekly while deriving benefit. The futility boundary was crossed at the interim analysis of Group A, resulting in a negative study. Parsaclisib monotherapy demonstrated an objective response rate (ORR) of 25.5% (8 complete metabolic responses/6 partial metabolic responses) and a median duration of response of 6.2 months. ORR in Group B was 20.0% (1 complete metabolic response). Parsaclisib monotherapy demonstrated manageable toxicities with no new safety signals reported. Further evaluation of parsaclisib in combination with standard therapies and active investigational agents is underway.

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Parsaclisib, a potent, selective, next‐generation PI3Kδ inhibitor, has shown clinical benefit in patients with relapsed or refractory B‐cell lymphoma. We undertook a phase Ib study (CITADEL‐111) evaluating safety, pharmacokinetics, and efficacy of parsaclisib in Japanese patients with relapsed or refractory B‐cell malignancies. Patients received oral parsaclisib daily for 8 weeks then once weekly (10‐mg dose, n = 3; 20‐mg dose, n = 14). Pharmacokinetic samples were collected on days 1, 8, and 15, and efficacy was monitored according to Lugano criteria. At data cut‐off (August 14, 2020), 6 patients (35.3%) remained on study treatment and 11 (64.7%) discontinued due to progressive disease (9 [52.9%]) or adverse events (2 [11.8%]). Median duration of treatment was 8.3 (range, 0.3–24.4) months. The most commonly reported nonhematologic adverse events were constipation (6 [35.3%]), nausea, and pyrexia (each 4 [23.5%]). Five patients (29.4%) experienced treatment‐emergent new or worsening decreased neutrophils to grade 3 or 4. No treatment‐emergent worsening in aminotransferase elevations to grade 3 or 4 were observed. Ten patients (58.8%) required dose interruption and 5 (29.4%) dose reduction. Body weight–normalized parsaclisib exposure was comparable between Japanese and Western patients. Objective response rate was 100% in follicular lymphoma (9 of 9 patients, including complete response in 2 patients [22.2%]) and marginal zone lymphoma (2 of 2 patients), and 16.7% in diffuse large B‐cell lymphoma (1 of 6 patients). Results observed in Japanese patients with relapsed or refractory follicular or marginal zone lymphoma support further clinical development of parsaclisib in these patient populations.

Precision medicine is the systematic use of information that pertains to an individual patient to select or optimize that patient's preventative and therapeutic care. Recent studies have classified biomarkers into predictive and prognostic biomarkers based on their roles in clinical studies. To design a clinical trial for precision medicine, predictive biomarkers and prognostic biomarkers should both be included. In statistical analysis, biomarkers are mathematically treated as covariates. We first classify covariates into predictive and prognostic covariates according to their roles. We then provide a brief review of recent advances in adaptive designs that incorporate covariates. However, the literature includes no designs that incorporate both prognostic covariates and predictive covariates simultaneously. In this paper, we propose a new family of covariate-adjusted response-adaptive (CARA) designs that incorporate both prognostic and predictive covariates and the responses. It is important to note that the predictive biomarkers and prognostic biomarkers play different roles in the new designs. The advantages of the proposed methods are demonstrated via numerical studies, and some further statistical issues are also discussed.