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BackgroundIn the United States, there has been a concerning rise in the prevalence of opioid use disorders (OUD) among transition-age (TA) adults, 18 to 25-years old, with a disproportionate impact on individuals and families covered by Medicaid. Of equal concern, the treatment system continues to underperform for many young people, emphasizing the need to address the treatment challenges faced by this vulnerable population at a pivotal juncture in their life course. Pharmacotherapy is the most effective treatment for OUD, yet notably, observational studies reveal gaps in the receipt of and retention in medications for opioid use disorder (MOUD), resulting in poor outcomes for many TA adults in treatment. Few current studies on OUD treatment quality explicitly consider the influence of individual, organizational, and contextual factors, especially for young people whose social roles and institutional ties remain in flux.MethodsWe introduce a retrospective, longitudinal cohort design to study treatment quality practices and outcomes among approximately 65,000 TA adults entering treatment for OUD between 2012 and 2025 in New York. We propose to combine data from multiple sources, including Medicaid claims and encounter data and a state registry of substance use disorder (SUD) treatment episodes, to examine three aspects of OUD treatment quality: 1) MOUD use, including MOUD option (e.g., buprenorphine, methadone, or extended-release [XR] naltrexone); 2) adherence to pharmacotherapy and retention in treatment; and 3) adverse events (e.g., overdoses). Using rigorous analytical methods, we will provide insights into how variation in treatment practices and outcomes are structured more broadly by multilevel processes related to communities, treatment programs, and characteristics of the patient, as well as their complex interplay.DiscussionOur findings will inform clinical decision making by patients and providers as well as public health responses to the rising number of young adults seeking treatment for OUD amidst the opioid and polysubstance overdose crisis in the U.S.

This paper reports the results of a four-state collaboration––Texas, New York, Virginia, and Illinois––that uses Student Unit Record Database Systems that track students from high school into college. The goal is to determine whether it is possible to accurately predict whether individual students will not graduate using very early indicators available at college entry or during the first semester. Using similar statistical models across four state university systems, we identify individual students at greatest risk of non-completion quite accurately at early stages, allowing college staff to prioritize interventions and supports aimed at improving completion for those at greatest risk. Our logistic regression models rely on variables available to university administrators at student entry, including high school GPA, standardized test scores, parental income, remediation requirements, declared major, and college credits attempted in the first semester. Our models do not use gender, race, or ethnicity in determining probability of non-completion, making them useful for public university administrators. The fact that the same factors accurately predict graduation and non-completion in four very different state contexts suggests that similar dynamics are at play across the country. Our findings suggest that current commercial products that require extensive effort from faculty to input data on student progress, to act as an early warning system, may be unnecessary. More easily obtainable data can accurately predict students at risk of non-completion.

Objectives: Several drug-drug interaction (DDI) checkers such as DDI-Predictor have been developed to detect and grade DDIs. DDI-Predictor gives an estimate of the magnitude of an interaction based on the ratio of areas under the curve. The objective of the present study was to analyse the frequencies of DDIs involving well-known strong interactors such as rifampicin and selective serotonin reuptake inhibitors (SSRIs), as reported by a clinical pharmacy team using DDI-Predictor, and the pharmacist intervention acceptance rate., Methods: The pharmacist intervention rate and the physician acceptance rate were calculated for DDIs involving rifampicin or the SSRIs fluoxetine, paroxetine, duloxetine and sertraline. The rates were compared with a bilateral χ 2 test or Fisher's exact test., Results: Of the 284 DDIs recorded, 38 (13.4%) involved rifampicin and 78 (27.5%) involved SSRIs. The pharmacist intervention rate differed significantly (68.4% for rifampicin vs 48.8% for SSRIs; p=0.045) but the physician acceptance rate did not (84.6% for rifampicin vs 81.6% for SSRIs; p=1). Pharmaceutical interventions for SSRIs were more frequent when the ratio of the area under the drug concentration versus time curve in DDI-Predictor was >2. Pharmacists were more likely to issue a pharmacist intervention for DDIs involving rifampicin because of a high perceived risk of treatment failure and were less likely to issue a pharmacist intervention for DDIs involving an SSRI, except when the suspected interaction was strong., Conclusions: DDI checkers can help pharmacists to manage DDIs involving strong interactors. DDIs involving strong inhibitors versus a strong inducer differ with regard to their intervention and acceptance rates, notably due to the estimation of the magnitude of the DDI., Competing Interests: Competing interests: None declared., (© European Association of Hospital Pharmacists 2024. No commercial re-use. See rights and permissions. Published by BMJ.)

Background: While more and more people tend to use herbal products thinking they are safer than conventional western medicine, the reality is other. If natural products are bio-active and possess potential therapeutic activities, then the benefit/risk balance should be considered like any other health product. Some herbs are known to have the potential to interact with patient's treatment and to cause adverse drug reactions. While these are scarce, they are potentially harmful, and can lead to major sequels and even death in some cases. Despite these known facts, little guidelines about how to evaluate the risk of interaction and to handle them exist in literature. Notably, few scales allowing to assess the risk of a specific combination of herbs and drugs exist., Method: We propose a new scoring method BABINE (Boosting Analysis of Bibliography for herb- drug INteraction Evaluation) and discuss a scale to evaluate this risk based on iterative rounds of experts' discussion., Results: After 6 rounds of case reports/clinical studies evaluation, we analyzed and synthesized criteria identified as important by the experts and developed a corresponding evaluation scale., Conclusion: Even if our scale greatly simplifies pharmacological events, we believe it provides a robust and transparent way to rapidly assess the risk of adverse event., Competing Interests: Declarations. No experiment has been done in this work on humans and/or the use of human tissue samples. Ethics approval and consent to participate: No human material or data was used during this study. Consent for publication: Not applicable. Informed consent: Not applicable. Competing interests: The authors declare no competing interests., (© 2024. The Author(s).)

To avoid the failures in therapy with psychotropic drugs, treatments can be personalized by applying the results of therapeutic drug monitoring and pharmacogenetic testing. The objective of the present single-center observational study was to describe the changes in psychotropic drug management prompted by therapeutic drug monitoring and pharmacogenetic testing, and to compare the effective drug concentration based on metabolic status with the dose predicted using an in silico decision tool for drug-drug interactions. The study was conducted in psychiatry wards at Lille University Hospital (Lille, France) between 2016 and 2020. Patients with data for at least one therapeutic drug monitoring session or pharmacogenetic test were included. Blood tests were performed for 490 inpatients (mainly indicated by treatment monitoring or failure) and mainly concerned clozapine (21.4%) and quetiapine (13.7%). Of the 617 initial therapeutic drug monitoring tests, 245 (40%) complied with good sampling practice. Of the patients, 51% had a drug concentration within the therapeutic range. Regardless of the drug concentration, the drug management did not change in 83% of cases. Thirty patients underwent pharmacogenetic testing (twenty-seven had also undergone therapeutic drug monitoring) for treatment failure; the plasma drug concentration was outside the reference range in 93% of cases. The patient's metabolic status explained the treatment failure in 12 cases (40%), and prompted a switch to a drug metabolized by another CYP450 pathway in 5 cases (42%). Of the six tests that could be analyzed with the in silico decision tool, all of the drug concentrations after adjustment were included in the range estimated by the tool. Knowledge of a patient's drug concentration and metabolic status (for CYD2D6 and CYP2C19) can help clinicians to optimize psychotropic drug adjustment. Drug management can be optimized with good sampling practice, support from a multidisciplinary team (a physician, a geneticist, and clinical pharmacist), and decision support tools.

Purpose: The objective was to develop a pharmacokinetic-pharmacodynamic (PK-PD) model linking everolimus and sorafenib exposure with biomarker dynamics and progression-free survival (PFS) based on data from EVESOR trial in patients with solid tumors treated with everolimus and sorafenib combination therapy and to simulate alternative dosing schedules for sorafenib., Patients and Methods: Everolimus (5-10 mg once daily, qd) and sorafenib (200-400 mg twice daily, bid) were administered according to four different dosing schedules in 43 solid tumor patients. Rich PK and PD sampling for serum angiogenesis biomarkers was performed. Baseline activation of RAS/RAF/ERK (MAPK) pathway was assessed by quantification of mRNA specific gene panel in tumor biopsies. The PK-PD modeling was performed using NONMEM ® software., Results: An indirect response PK-PD model linking sorafenib plasma exposure with soluble vascular endothelial growth factor receptor 2 (sVEGFR2) dynamics was developed. Progression-free survival (PFS) was described by a parametric time-to-event model. Higher decreases in sVEGFR2 at day 21 and higher baseline activation of MAPK pathway were associated with longer PFS (p = 0.002 and p = 0.007, respectively). The simulated schedule sorafenib 200 mg bid 5 days-on/2 days-off + continuous everolimus 5 mg qd was associated with median PFS of 4.3 months (95% CI 1.6-14.4), whereas the median PFS in the EVESOR trial was 3.6 months (95% CI 2.7-4.2, n = 43)., Conclusion: Sorafenib 200 mg bid 5 days-on/2 days-off + everolimus 5 mg qd continuous was selected for an additional arm of EVESOR trial to evaluate whether this simulated schedule is associated with higher clinical benefit., Trial Registration: ClinicalTrials.gov Identifier: NCT01932177., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Purpose: Everolimus (EVE) and sorafenib (SOR) combination was associated with synergistic activity in preclinical models. However, previous clinical studies were hampered by cumulative toxicities when both were given continuously. The academic EVESOR trial (NCT01932177) was designed to assess alternative doses and intermittent dosing schedules of EVE and SOR combination therapy to improve the benefit-risk ratio for patients with solid tumors., Methods: EVESOR is a multiparameter dose-escalation phase I trial investigating different doses and dosing schedules, with the final objective of generating data for modeling and simulation. Patients were allocated into continuous (A and B) or intermittent (C and D) schedules to determine the recommended phase II dose (RP2D). The clinical outcomes are presented here., Results: Forty-three patients were included from 2013 to 2019. Most of them had gynecological (25.6%), cholangiocarcinomas (23.2%), colorectal (14.0%), and breast cancers (11.6%). Dose-escalation up to EVE 10 mg QD and SOR 400 mg BID was possible on intermittent schedules. Five dose-limiting toxicities were observed, and dose reductions were required in 39.5% patients, stabilizing at EVE 5 mg and SOR 200 mg BID for 58.1% of them. The overall response rate was 6.3%, and disease control rate was 75.0%. The median progression-free survival (PFS) was 3.6 months. The longest median PFS were observed in cholangiocarcinomas (9.9 months), and gynecological adenocarcinomas (9.2 months)., Conclusion: Intermittent arms were associated with improved efficacy/toxicity profiles; and EVE 5 mg QD and SOR 200 mg BID was defined a clinically feasible dose. Strong signs of efficacy were found in cholangiocarcinomas and gynecologic carcinomas., Trial Registration: ClinicalTrials.gov Identifier: NCT01932177., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Background and Objective: Chronic kidney disease (CKD) may alter drug renal elimination but is also known for interacting with hepatic metabolism via multiple uremic components. However, few global models, considering the five major cytochromes, have been published, and none specifically address the decrease in cytochrome P450 (CYP450) activity. The aim of our study was to estimate the possibility of quantifying residual cytochrome activity as a function of filtration rate, according to the data available in the literature., Methods: For each drug in the DDI-predictor database, we collected available pharmacokinetic data comparing drug exposition in the healthy patient and in various stages of CKD, before building a model capable of predicting the variation of exposure according to the degree of renal damage. We followed an In vivo Mechanistic Static Model (IMSM) approach, previously validated for predicting change in liver clearance. We estimated the remaining fraction parameters at glomerular filtration rate (GFR) = 0 and the alpha value of GFR to 50% impairment for the 5 major cytochromes using a non-linear constrained regression using Matlab software., Results: Thirty-one compounds had usable pharmacokinetic data, with 51 AUC ratios between healthy and renal impaired patients. The remaining CYP3A4 activity was estimated to be 0.4 when CYP2D6, 2C9, 2C19 and 1A2 activity was estimated to be 0.43; 1; 0.73 and 0.7, respectively. The alpha value was estimated to be at 6.62; 25; 9.8; 1.38 and 11.04 for each cytochrome. In comparison with published data, all estimates but one were correctly predicted in the range of 0.5-2., Conclusion: Our approach was able to describe the impact of CKD on metabolic elimination. Modelling this process makes it possible to anticipate changes in clearance and drug exposure in CKD patients, with the advantage of greater simplicity than approaches based on physiologically-based pharmacokinetic modelling. However, a precise estimation of the impact of renal failure is not possible with an IMSM approach due to the large variability of the published data, and thus should rely on specific pharmacokinetic modelling for narrow therapeutic margin drugs., (© 2023. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

Protein kinase inhibitors share pharmacokinetic (PK) pathways among themselves. They are all metabolized by several cytochromes P450 (CYP). For most of them, CYP3A4 is the predominant metabolic pathway. However, their oral bioavailability differs. For example, the oral bioavailability of imatinib has been estimated at nearly 100%, but that of ibrutinib averages 3% due to its high hepatic first-pass effect. Overall, the smaller the oral bioavailability, the larger its interindividual PK variability. Indeed, for drugs with low oral bioavailability, the extent of their absorption is an additional cause (along with elimination variability) of differences in drug exposure among patients. The impact of drug-drug interaction (DDI) also differs between drugs with low or high oral bioavailability. We describe and explain why the impact of CYP3A4 inhibitors and inducers is much greater for protein kinase inhibitors with low oral bioavailability. The effect of food on protein kinase inhibitors and DDIs corresponding to plasma protein binding will also be considered. Finally, the benefits of these concepts in clinical practice (including therapeutic drug monitoring) will be discussed. Overall, our main objective was to apply fundamental PK concepts to understanding the main clinical issues of these oral anticancer drugs., (© 2023. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

Background: Anti-angiogenic rechallenge with bevacizumab plus chemotherapy is effective in recurrent ovarian cancer (rOC); however, data are limited on tyrosine kinase inhibitors after progression on maintenance bevacizumab., Methods: In the randomized phase II TAPAZ trial, patients with rOC during the first year of bevacizumab maintenance therapy were assigned 2:1 to either weekly paclitaxel 65 mg/m 2 plus pazopanib 600-800 mg daily or standard weekly paclitaxel 80 mg/m 2 . The primary endpoint was 4-month progression-free survival (PFS) rate., Results: Overall, 116 patients were randomized and treated: 79 with combination therapy and 37 with single-agent paclitaxel. Median follow-up was 13.1 months. There was no difference between treatment arms in 4-month PFS rate (61% [95% CI, 51-73%] with the combination versus 68% [95% CI, 54-85%] with paclitaxel alone), median PFS (4.9 [95% CI, 4.1-6.1] versus 5.8 [95% CI, 4.8-7.4] months, respectively) or median overall survival (13.6 versus 12.9 months, respectively). The combination was associated with more grade 3/4 toxicities (87% versus 70%, respectively) and toxicity-related paclitaxel discontinuations (22% versus 11%). Pazopanib was discontinued for toxicity in 44% of patients, most commonly for gastrointestinal and vascular events. There were two treatment-related deaths, both in the combination arm (pulmonary embolism and gastrointestinal perforation). At month 4, patient-reported outcomes deteriorated from baseline in the combination arm, particularly for abdominal/gastrointestinal symptoms, which showed a clinically important difference versus paclitaxel alone., Conclusions: In rOC progressing during maintenance bevacizumab, adding pazopanib to paclitaxel did not improve efficacy, increased toxicity, and compromised chemotherapy delivery., Clinicaltrials: govregistration:NCT02383251., (Copyright © 2022 Elsevier Inc. All rights reserved.)

Background: Obesity increases the risk of type 2 diabetes, heart disease, stroke, mobility problems and some cancers, and its prevalence is rising. Men engage less than women in existing weight loss interventions. Game of Stones builds on a successful feasibility study and aims to find out if automated text messages with or without endowment incentives are effective and cost-effective for weight loss at 12 months compared to a waiting list comparator arm in men with obesity., Methods: A 3-arm, parallel group, assessor-blind superiority randomised controlled trial with process evaluation will recruit 585 adult men with body mass index of 30 kg/m 2 or more living in and around three UK centres (Belfast, Bristol, Glasgow), purposively targeting disadvantaged areas. Intervention groups: (i) automated, theory-informed text messages daily for 12 months plus endowment incentives linked to verified weight loss targets at 3, 6 and 12 months; (ii) the same text messages and weight loss assessment protocol; (iii) comparator group: 12 month waiting list, then text messages for 3 months. The primary outcome is percentage weight change at 12 months from baseline. Secondary outcomes at 12 months are as follows: quality of life, wellbeing, mental health, weight stigma, behaviours, satisfaction and confidence. Follow-up includes weight at 24 months. A health economic evaluation will measure cost-effectiveness over the trial and over modelled lifetime: including health service resource-use and quality-adjusted life years. The cost-utility analysis will report incremental cost per quality-adjusted life years gained. Participant and service provider perspectives will be explored via telephone interviews, and exploratory mixed methods process evaluation analyses will focus on mental health, multiple long-term conditions, health inequalities and implementation strategies., Discussion: The trial will report whether text messages (with and without cash incentives) can help men to lose weight over 1 year and maintain this for another year compared to a comparator group; the costs and benefits to the health service; and men's experiences of the interventions. Process analyses with public involvement and service commissioner input will ensure that this open-source digital self-care intervention could be sustainable and scalable by a range of NHS or public services., Trial Registration: ISRCTN 91974895 . Registered on 14/04/2021., (© 2022. The Author(s).)

Introduction: Iatrogeny due to drug-drug interactions is insufficiently documented, due to the high number of possible combinations., Objective: This study aimed to design a simple but general method to predict the variation of adverse events (AE) frequency due to a pharmacokinetic or pharmacodynamic interaction., Methods: Three prediction models were designed using a logistic probability density function. Each prediction model was based on three components: the AE odds ratio of each drug in the combination, and the area under the curve ratio (Rauc) of the pharmacokinetic interaction, if any. Pharmacodynamic interaction was assumed to be additive on logit scale. Rauc was predicted using a well-validated mechanistic static model, freely available online. No combination study is required. The method was evaluated against a wide range of AEs (28 High Level Terms) and 211 drug combinations (involving 43 victim drugs and 55 perpetrators), by comparing the observed and predicted frequencies. The observed odds ratios were estimated with a disproportionality analysis from the FDA Adverse Event Reporting System, using an approach that minimizes biases., Results: With the best model, the rate of prediction considered as correct (within 50-200% of the observed value) was 72%, and the bias was negligible (-5%). The AE odds ratio due to pharmacokinetic and pharmacodynamic interactions was equally well predicted., Conclusions: A simple workflow to implement the method in practice is proposed. This method may help to foresee and to anticipate the harmful consequences associated with drug-drug interactions, at virtually no experimental cost, when the odds ratio of an AE is known for each drug alone and the AUC ratio is known or predicted by a suitable model., (© 2022. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

Background: In ovarian carcinomas, the likelihood of disease cure following first-line medical-surgical treatment has been poorly addressed. The objective was to: (a) assess the likelihood of long-term disease-free (LDF) > 5 years; and (b) evaluate the impact of the tumour primary chemosensitivity (assessed with the modelled CA-125 KELIM) with respect to disease stage, and completeness of debulking surgery., Methods: Three Phase III trial datasets (AGO-OVAR 9; AGO-OVAR 7; ICON-7) were retrospectively investigated in an "adjuvant dataset", whilst the Netherlands Cancer Registry was used in a "neoadjuvant dataset". The prognostic values of KELIM, disease stage and surgery outcomes regarding the likelihood of LDF were assessed using univariate/multivariate analyses., Results: Of 2029 patients in the "adjuvant dataset", 82 (4.0%) experienced LDF (Stage I-II: 25.9%; III: 2.1%; IV: 0.5%). Multivariate analyses identified disease stage and KELIM (OR = 4.24) as independent prognostic factors. Among the 1452 patients from the "neoadjuvant dataset", 36 (2.4%) had LDF (Stage II-III: 3.3%; IV: 1.3%). Using multivariate tests, high-risk diseases (OR = 0.18) and KELIM (OR = 2.96) were significant., Conclusion: The probability of LDF > 5 years after first-line treatment in 3486 patients (<4%) was lower than thought. These data could represent a reference for future studies meant to assess progress related to PARP inhibitors., (© 2022. The Author(s).)

Tusamitamab ravtansine (SAR408701) is an antibody-drug conjugate (ADC), combining a humanized monoclonal antibody (IgG1) targeting carcinoembryonic antigen-related cell adhesion molecule 5 (CEACAM5) and a potent cytotoxic maytansinoid derivative, DM4, inhibiting microtubule assembly. SAR408701 is currently in clinical development for the treatment of advanced solid tumors expressing CEACAM5. It is administered intravenously as a conjugated antibody with an average Drug Antibody Ratio (DAR) of 3.8. During SAR408701 clinical development, four entities were measured in plasma: conjugated antibody (SAR408701), naked antibody (NAB), DM4 and its methylated metabolite (MeDM4), both being active. Average DAR and proportions of individual DAR species were also assessed in a subset of patients. An integrated and semi-mechanistic population pharmacokinetic model describing the time-course of all entities in plasma and DAR measurements has been developed. All DAR moieties were assumed to share the same drug disposition parameters, excepted for clearance which differed for DAR0 (i.e. NAB entity). The conversion of higher DAR to lower DAR resulted in a DAR-dependent ADC deconjugation and was represented as an irreversible first-order process. Each conjugated antibody was assumed to contribute to DM4 formation. All data were fitted simultaneously and the model developed was successful in describing the pharmacokinetic profile of each entity. Such a structural model could be translated to other ADCs and gives insight of mechanistic processes governing ADC disposition. This framework will further be expanded to evaluate covariates impact on SAR408701 pharmacokinetics and its derivatives, and thus can help identifying sources of pharmacokinetic variability and potential efficacy and safety pharmacokinetic drivers., (© 2022. The Author(s).)

Tusamitamab ravtansine is an anti-CEACAM5 antibody-drug conjugate indicated in patients with solid tumors. Based on a previous developed semimechanistic model describing simultaneously pharmacokinetic (PK) of SAR408701, two of its active metabolites: DM4 and methyl-DM4 and naked antibody, with integration of drug-to-antibody data, the main objective of the present analysis was to evaluate covariate's impact in patients from phase I/II study (n = 254). Demographic and pathophysiologic baseline covariates were explored to explain interindividual variability on each entity PK parameter. Model parameters were estimated with good precision. Five covariates were included in the final PK model: body surface area (BSA), tumor burden, albumin, circulating target, and gender. Comparison of BSA-adjusted dosing and flat dosing supported the current BSA-based dosing regimen, to limit under and over exposure in patients with extreme BSA. Overall, this model characterized accurately the PKs of all entities and highlighted sources of PK variability. By integrating mechanistic considerations, this model aimed to improve understanding of the SAR408701 complex disposition while supporting key steps of clinical development., (© 2022 The Authors. CPT: Pharmacometrics & Systems Pharmacology published by Wiley Periodicals LLC on behalf of American Society for Clinical Pharmacology and Therapeutics.)

Background: In metastatic prostate cancer (PCa) patients, androgen-deprivation therapy (ADT) combined with chemotherapy or next-generation androgen receptor targeted agents is a new standard treatment. The objective of the present study is to assess longitudinal PSA kinetics during treatment using mathematical modeling, to identify the modeled PSA kinetic parameters able to exhibit early prognostic/predictive values., Methods: Phase III clinical trial dataset (NCT00764166) comparing ADT +/- docetaxel in 250 locally treated patients for PCa with rising PSA levels, who were at high risk of metastatic disease was assessed. A kinetic-pharmacodynamic (K-PD) model was used to fit PSA kinetics during the first 100 treatment days, to estimate the modeled PSA production rate K (KPROD) and elimination constant rate K (KELIM). The prognostic value of these parameters, considered as categorized (favorable vs. unfavorable) covariates regarding PSA progression-free survival (PSA-PFS) and overall survival (OS), was assessed using univariate/multivariate analyses., Results: Data from 177/250 patients was assessed. KELIM exhibited a significant prognostic value regarding PSA-PFS and KPROD regarding OS (univariate analysis). In the PSA-PFS final multivariate model, KELIM and the primary therapy type were significant. The OS multivariate model integrated both KPROD and baseline PSA doubling-time., Conclusion: In this first study assessing the modeled PSA kinetics prognostic value in PCa patients treated with systemic treatments, KELIM and KPROD exhibited respective prognostic values regarding PSA-PFS and OS.