Health-related Quality of Life in Patients with Previously Treated Advanced Urothelial Carcinoma from EV-301: A Phase 3 Trial of Enfortumab Vedotin Versus Chemotherapy.

BACKGROUND AND OBJECTIVE: In comparison to chemotherapy, enfortumab vedotin (EV) prolonged overall survival in patients with previously treated advanced urothelial carcinoma in EV-301. The objective of the present study was to assess patient experiences of EV versus chemotherapy using patient-reported outcome (PRO) analysis of health-related quality of life (HRQoL). METHODS: For patients in the phase 3 EV-301 trial randomized to EV or chemotherapy we assessed responses to the validated European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire Core 30 (QLQ-C30) at baseline, weekly for the first 12 wk, and then every 12 wk until discontinuation. We analyzed the QLQ-C30 change from baseline to week 12, the confirmed improvement rate, and the time to improvement or deterioration. KEY FINDINGS AND LIMITATIONS: Baseline PRO compliance rates were 91% for the EV arm (n = 301) and 89% for the chemotherapy arm (n = 307); the corresponding average rates from baseline to week 12 were 70% and 67%. Patients receiving EV versus chemotherapy had reduced pain (difference in change from baseline to week 12: -5.7, 95% confidence interval [CI] -10.8 to -0.7; p = 0.027) and worsening appetite loss (7.3, 95% CI 0.90-13.69; p = 0.026). Larger proportions of patients in the EV arm reported HRQoL improvement from baseline than in the chemotherapy arm; the odds of a confirmed improvement across ten QLQ-C30 function/symptom scales were 1.67 to 2.76 times higher for EV than for chemotherapy. Patients in the EV arm had a shorter time to first confirmed improvement in global health status (GHS)/QoL, fatigue, pain, and physical, role, emotional, and social functioning (all p < 0.05). EV delayed the time to first confirmed deterioration in GHS/QoL (p = 0.027), but worsening appetite loss occurred earlier (p = 0.009) in comparison to chemotherapy. CONCLUSIONS AND CLINICAL IMPLICATIONS: HRQoL with EV was maintained, and deterioration in HRQoL was delayed with EV in comparison to chemotherapy. Better results with EV were reported for some scales, with the greatest difference observed for pain. These findings reinforce the EV safety and efficacy outcomes and benefits observed in EV-301. PATIENT SUMMARY: Patients with previously treated advanced cancer of the urinary tract receiving the drug enfortumab vedotin maintained their HRQoL in comparison to patients treated with chemotherapy. The EV-301 trial is registered on ClinicalTrials.gov as NCT03474107 and on EudraCT as 2017-003344-21.

Reflections on estimands for patient-reported outcomes in cancer clinical trials.

It is common and important to include the patient's perspective of the impact of treatment on health-related quality of life (HRQoL) outcomes. In this commentary, we focus on applying the new addendum to ICH E9 guideline E9 (R1) relating to the estimand framework to Patient Reported Outcomes (PROs) collected in cancer clinical trials, from a statistician's viewpoint. Currently, common practice for statistical analysis of PRO endpoints of published cancer clinical trials demonstrates ambiguity, leaving critical questions unspecified, hindering conclusions about the effect of treatment on PRO endpoints as well as comparability between clinical trials. To avoid this scenario, we advocate the systematic use of the estimand framework which requires the prospective definition of clear PRO research questions. Among the five attributes of the estimands framework, the definition of the endpoint (what is the right PRO measure and timeframe to target and why?), the intercurrent event identification and management (what happens with PRO data post-disease progression, what is the impact of death?) and the population-level summary (what is an acceptable statistical summary for PRO data?) require the most attention for PRO estimands. We identify good practice and highlight discussion points including the challenges of statistical analysis in the presence of missing and/or unobservable data and in relation to death. Through this discussion we highlight that there is no "statistical magic", but that the estimand framework will help you find out what you really want to know when quantifying the benefit of treatments from the patients' perspective.

Time to deterioration of patient-reported outcomes in non-small cell lung cancer: exploring different definitions.

PURPOSE: The clinical relevance of different time-to-deterioration (TTD) definitions for patient-reported outcomes were explored. METHODS: TTD definitions differing by reference score and deterioration event were used to analyse data from the phase 3 FLAURA trial of first-line osimertinib versus erlotinib or gefitinib in patients with EGFR-mutated advanced non-small cell lung cancer. Pre-specified key symptoms were fatigue, appetite loss, cough, chest pain and dyspnoea, scored using the European Organisation for Research and Treatment of Cancer QLQ-C30 and QLQ-LC13 questionnaires (≥ 10-point difference = clinically relevant). RESULTS: No significant treatment differences in TTD (distributions) were observed using definitions based on transient or definitive deterioration alone. TTD definitions based on definitive, sustained deterioration, with death not included as an event, yielded a significant treatment difference for dyspnoea (hazard ratio [HR] 0.71; P = 0.034) when baseline was the reference, and for cough (HR 0.70; P = 0.009) and dyspnoea (HR 0.71; P = 0.004) when best previous score was the reference. With death included as an event, treatment differences were significant for dyspnoea (HR 0.70; P = 0.025) when baseline was the reference, and for cough (HR 0.70; P = 0.011), dyspnoea (HR 0.71; P = 0.003) and chest pain (HR 0.71; P = 0.038) when best previous score was the reference. Irrespective of definition, TTD for appetite loss and fatigue did not differ significantly between arms. CONCLUSION: This exploratory work showed that different TTD definitions yield different magnitudes of treatment difference, highlighting the importance of pre-specifying TTD definitions upfront in clinical trials. CLINICAL TRIAL REGISTRATION: ClinicalTrials.gov NCT02296125.

Effects of Trilaciclib on Chemotherapy-Induced Myelosuppression and Patient-Reported Outcomes in Patients with Extensive-Stage Small Cell Lung Cancer: Pooled Results from Three Phase II Randomized, Double-Blind, Placebo-Controlled Studies.

BACKGROUND: Chemotherapy-induced myelosuppression (CIM) and its sequalae cause significant side effects and harm to quality of life. Trilaciclib is an intravenous CDK4/6 inhibitor that is administered prior to chemotherapy to protect hematopoietic stem and progenitor cells from chemotherapy-induced damage (myeloprotection). PATIENTS AND METHODS: Data from three randomized, double-blind, placebo-controlled studies (NCT02499770, NCT03041311, and NCT02514447) were pooled to evaluate the effects of trilaciclib administered prior to standard-of-care chemotherapy (first-line etoposide plus carboplatin [E/P], first-line E/P plus atezolizumab, and second-/third-line topotecan) in patients with extensive-stage small cell lung cancer (ES-SCLC). The primary endpoints were duration of severe neutropenia (absolute neutrophil count < 0.5 × 109 cells/L) in cycle 1 and occurrence of severe neutropenia. Additional prespecified endpoints further assessed the effect of trilaciclib on myeloprotection, health-related quality of life (HRQoL), antitumor efficacy, and safety. RESULTS: Of 242 randomized patients, 123 received trilaciclib and 119 received placebo. Compared with placebo, administration of trilaciclib prior to chemotherapy resulted in significant decreases in most measures of multilineage CIM. The reduction in hematologic toxicity translated into the reduced need for supportive care interventions and hospitalizations due to CIM or sepsis and improvements in HRQoL domains related to the protected cell lineages, including fatigue, physical wellbeing, and functional wellbeing. Antitumor efficacy was similar for patients receiving trilaciclib or placebo. CONCLUSION: Administering trilaciclib prior to chemotherapy resulted in clinically meaningful reductions in CIM and its consequences and improved patient HRQoL, with no impact on the antitumor efficacy of three individual chemotherapy regimens used in the first- or second-/third-line treatment of ES-SCLC.

The association between health-related quality-of-life scores and clinical outcomes in metastatic castration-resistant prostate cancer patients: Exploratory analyses of AFFIRM and PREVAIL studies.

BACKGROUND: Our exploratory analysis examined the association between health-related quality of life (HRQoL) (baseline and change over time) and clinical outcomes (overall survival [OS]/radiographic progression-free survival [rPFS]) in metastatic castration-resistant prostate cancer (mCRPC). METHODS: HRQoL, OS and rPFS were assessed in phase III trials comparing enzalutamide with placebo in chemotherapy-naïve (PREVAIL; NCT01212991) or post-chemotherapy (AFFIRM; NCT00974311) mCRPC. HRQoL was assessed using the Functional Assessment of Cancer Therapy-Prostate (FACT-P). Multivariate analyses evaluated the prognostic significance of baseline and time-dependent scores after adjusting for treatment and clinical/demographic variables. Hazard ratios (HRs) and 95% confidence intervals (CIs) represented the hazard of rPFS or OS per minimally important difference (MID) score change in HRQoL variables. RESULTS: In baseline and time-dependent multivariate analyses, OS was independently associated with multiple HRQoL measures across both studies. In time-dependent analyses, a 10-point (upper bound of MID range) increase (improvement) in FACT-P total score was associated with reductions in mortality risk of 19% in AFFIRM (HR 0.81 [95% CI 0.78-0.84]) and 21% in PREVAIL (HR 0.79 [0.76-0.83]). For baseline analyses, a 10-point increase in FACT-P total score was associated with reductions in mortality risk of 12% (HR 0.88 [0.84-0.93]) and 10% (HR 0.90 [0.86-0.95]) in AFFIRM and PREVAIL, respectively. rPFS was associated with a subset of HRQoL domains in both studies. CONCLUSION: Several baseline HRQoL domains were prognostic for rPFS and OS in patients with mCRPC, and this association was maintained during treatment, indicating that changes in HRQoL are informative for patients' expected survival.

Adjusting Overall Survival Estimates after Treatment Switching: a Case Study in Metastatic Castration-Resistant Prostate Cancer.

BACKGROUND: If patients in oncology trials receive subsequent therapy, standard intention-to-treat (ITT) analyses may inaccurately estimate the overall survival (OS) effect of the investigational product. In this context, a post-hoc analysis of the phase 3 PREVAIL study was performed with the aim to compare enzalutamide with placebo in terms of OS, adjusting for potential confounding from switching to antineoplastic therapies that are not part of standard metastatic castration-resistant prostate cancer (mCRPC) treatment pathways in some jurisdictions. METHODS: The PREVAIL study, which included 1717 chemotherapy-naïve men with mCRPC randomized to treatment with enzalutamide 160 mg/day or placebo, was stopped after a planned interim survival analysis revealed a benefit in favor of enzalutamide. Data from this cutoff point were confounded by switching from both arms and so were evaluated in terms of OS using two switching adjustment methods: the two-stage accelerated failure time model (two-stage method) and inverse probability of censoring weights (IPCW). RESULTS: Following adjustment for switching to nonstandard antineoplastic therapies by 14.8 (129/872 patients) and 21.3% (180/845 patients) of patients initially randomized to enzalutamide and placebo, respectively, the two-stage and IPCW methods both resulted in numerical reductions in the hazard ratio (HR) for OS [HR 0.66, 95% confidence interval (CI) 0.57-0.81 and HR 0.63, 95% CI 0.52-0.75, respectively] for enzalutamide compared to placebo versus the unadjusted ITT analysis (HR 0.71, 95% CI 0.60-0.84). These results suggest a slightly greater effect of enzalutamide on OS than originally reported. CONCLUSION: In the PREVAIL study, switching to nonstandard antineoplastic mCRPC therapies resulted in the ITT analysis of primary data underestimating the benefit of enzalutamide on OS.

Evaluation of Serial Arterial Lactate Levels as a Predictor of Hospital and Long-Term Mortality in Patients After Cardiac Surgery.

OBJECTIVES: Although hyperlactatemia is common after cardiac surgery, its value as a prognostic marker is unclear. The aim of the present study was to determine whether postoperative serial arterial lactate (AL) measurements after cardiac surgery could predict outcome. DESIGN: Prospective, observational study. SETTING: Surgical intensive care unit in a tertiary-level university hospital. PARTICIPANTS: Participants included 2,935 consecutive patients. INTERVENTIONS: AL was measured on admission to the intensive care unit and 6, 12, and 24 hours after surgery, and evaluated together with clinical data and outcomes including in-hospital and long-term mortality. MEASUREMENTS AND MAIN RESULTS: In-hospital and long-term mortality (mean follow-up 6.3±1.7 years) were 5.9% and 8.7%, respectively. Compared with survivors, nonsurvivors showed higher mean AL values in all measurements (p<0.001). Hyperlactatemia (AL>3.0 mmol/L) was a predictor for in-hospital mortality (odds ratio = 1.468; 95% confidence interval = 1.239-1.739; p<0.001) and long-term mortality (hazard ratio = 1.511; 95% confidence interval = 1.251-1.825; p<0.001). Recent myocardial infarction and longer cardiopulmonary bypass time were predictors of hyperlactatemia. The pattern of AL dynamics was similar in both groups, but nonsurvivors showed higher AL values, as confirmed by repeated measures analysis of variance (p<0.001). The area under the curve also showed higher levels of AL in nonsurvivors (80.9±68.2 v 49.71±25.8 mmol/L/h; p = 0.038). Patients with hyperlactatemia were divided according to their timing of peak AL, with higher mortality and worse survival in patients in whom AL peaked at 24 hours compared with other groups (79.1% v 86.7%-89.2%; p = 0.03). CONCLUSIONS: The dynamics of the postoperative AL curve in patients undergoing cardiac surgery suggests a similar mechanism of hyperlactatemia in survivors and nonsurvivors, albeit with a higher production or lower clearance of AL in nonsurvivors. The presence of a peak of hyperlactatemia at 24 hours is associated with higher in-hospital and long-term mortality.

Effect of enzalutamide on health-related quality of life, pain, and skeletal-related events in asymptomatic and minimally symptomatic, chemotherapy-naive patients with metastatic castration-resistant prostate cancer (PREVAIL): results from a randomised, phase 3 trial.

BACKGROUND: Enzalutamide significantly increased overall survival and radiographic progression-free survival compared with placebo in the PREVAIL trial of asymptomatic and minimally symptomatic, chemotherapy-naive patients with metastatic castration-resistant prostate cancer. We report the effect of enzalutamide on health-related quality of life (HRQoL), pain, and skeletal-related events observed during this trial. METHODS: In this phase 3, double-blind trial, patients were randomly assigned (1:1) to receive enzalutamide 160 mg/day (n=872) or placebo (n=845) orally. HRQoL was assessed at baseline and during treatment using the Functional Assessment of Cancer Therapy-Prostate (FACT-P) and EQ-5D questionnaires. Pain status was assessed at screening, baseline, week 13, and week 25 with the Brief Pain Inventory Short Form (BPI-SF). The primary analysis of HRQoL data used a mixed-effects model to test the difference between least square means change from baseline at week 61. We assessed change from baseline, percentage improvement, and time to deterioration in HRQoL and pain, the proportion of patients with a skeletal-related event, and time to first skeletal-related event. Analysis was done on the intention-to-treat population. This study is registered with ClinicalTrials.gov, number NCT01212991. FINDINGS: Median treatment duration was 16·6 months (IQR 10·1-21·1) in the enzalutamide group and 4·6 months (2·8-9·7) in the placebo group. The mixed-effects model analyses showed significant treatment differences in change from baseline to week 61 with enzalutamide compared with placebo for most FACT-P endpoints and EQ-5D visual analogue scale. Median time to deterioration in FACT-P total score was 11·3 months (95% CI 11·1-13·9) in the enzalutamide group and 5·6 months (5·5-5·6) in the placebo groups (hazard ratio [HR] 0·62 [95% CI 0·54-0·72]; p<0·0001). A significantly greater proportion of patients in the enzalutamide group than in the placebo group reported clinically meaningful improvements in FACT-P total score (327 [40%] of 826 vs 181 [23%] of 790), in EQ-5D utility index (224 [28%] of 812 vs 99 [16%] of 623), and visual analogue scale (218 [27%] of 803 vs 106 of [18%] 603; all p<0·0001). Median time to progression in BPI-SF pain at its worst was 5·7 months (95% CI 5·6-5·7) in the enzalutamide group and 5·6 months (5·4-5·6) in the placebo group (HR 0·62 [95% CI 0·53-0·74]; p<0·0001). Progression of pain at its worst was less common in the enzalutamide group than in the placebo group at week 13 (220 [29%] of 769 vs 257 [42%] of 610; p<0·0001), but not at week 25 (225 [32%] of 705 vs 135 [38%] of 360; p=0·068). 278 (32%) of 872 patients in the enzalutamide group and 309 (37%) of 845 patients in the placebo group had experienced a skeletal-related event by data cutoff. Median time to first skeletal-related events in the enzalutamide group was 31·1 months (95% CI 29·5-not reached) and 31·3 months (95% CI 23·9-not reached) in the placebo group (HR 0·72 [95% CI 0·61-0·84]; p<0·0001). INTERPRETATION: In addition to improving overall survival relative to placebo, enzalutamide significantly improves patient-related outcomes and delays occurrence of first skeletal-related event in chemotherapy-naive men with metastatic castration-resistant prostate cancer. FUNDING: Astellas Pharma and Medivation.

The influence of body mass index on outcomes in patients undergoing cardiac surgery: does the obesity paradox really exist?

PURPOSE: Obesity influences risk stratification in cardiac surgery in everyday practice. However, some studies have reported better outcomes in patients with a high body mass index (BMI): this is known as the obesity paradox. The aim of this study was to quantify the effect of diverse degrees of high BMI on clinical outcomes after cardiac surgery, and to assess the existence of an obesity paradox in our patients. METHODS: A total of 2,499 consecutive patients requiring all types of cardiac surgery with cardiopulmonary bypass between January 2004 and February 2009 were prospectively studied at our institution. Patients were divided into four groups based on BMI: normal weight (18.5-24.9 kg∙m-2; n = 523; 21.4%), overweight (25-29.9 kg∙m-2; n = 1150; 47%), obese (≥ 30-≤ 34.9 kg∙m-2; n = 624; 25.5%) and morbidly obese (≥ 35kg∙m-2; n = 152; 6.2%). Follow-up was performed in 2,379 patients during the first year. RESULTS: After adjusting for confounding factors, patients with higher BMI presented worse oxygenation and better nutritional status, reflected by lower PaO2/FiO2 at 24h and higher albumin levels 48 h after admission respectively. Obese patients showed a higher risk for Perioperative Myocardial Infarction (OR: 1.768; 95% CI: 1.035-3.022; p = 0.037) and septicaemia (OR: 1.489; 95% CI: 1.282-1.997; p = 0.005). In-hospital mortality was 4.8% (n = 118) and 1-year mortality was 10.1% (n = 252). No differences were found regarding in-hospital mortality between BMI groups. The overweight group showed better 1-year survival than normal weight patients (91.2% vs. 87.6%; Log Rank: p = 0.029. HR: 1.496; 95% CI: 1.062-2.108; p = 0.021). CONCLUSIONS: In our population, obesity increases Perioperative Myocardial Infarction and septicaemia after cardiac surgery, but does not influence in-hospital mortality. Although we found better 1-year survival in overweight patients, our results do not support any protective effect of obesity in patients undergoing cardiac surgery.

Mapping the FACT-P to the preference-based EQ-5D questionnaire in metastatic castration-resistant prostate cancer.

OBJECTIVES: To develop a mapping algorithm for estimating EuroQol five-dimensional (EQ-5D) questionnaire values from the prostate cancer-specific health-related quality-of-life (HRQOL) instrument Functional Assessment of Cancer Therapy-Prostate (FACT-P) instrument. METHODS: The EQ-5D questionnaire and FACT-P instrument data were collected for a subset of patients with metastatic castration-resistant prostate cancer in a multicenter, randomized, double-blind, placebo-controlled phase 3 trial. We compared three statistical techniques to estimate patients' EQ-5D questionnaire index scores determined by using the UK tariff: 1) generalized estimating equations, 2) two-part model combining logistic regression and generalized estimating equation, and 3) separate mapping algorithms for patients with poor health defined as a FACT-P score of 76 or less (group-specific model). Four different sets of explanatory variables were compared. The models were cross-validated by using a 10-fold in-sample cross-validation. RESULTS: Values for both instruments were available for 236 patients with metastatic castration-resistant prostate cancer. The group-specific model including the FACT-P subscale scores and baseline variables had the best predictive performance with R(2) 0.718, root mean square error 0.162, and mean absolute error 0.117. The two-part model and the generalized estimating equation model including the FACT-P subdomain scores and baseline variables also had good predictive performance. CONCLUSIONS: The developed algorithms for mapping the FACT-P instrument to the EQ-5D questionnaire enable the estimation of preference-based health-related quality-of-life scores for use in cost-effectiveness analyses when directly elicited EQ-5D questionnaire data are missing.

Evaluation of the PaO2/FiO2 ratio after cardiac surgery as a predictor of outcome during hospital stay.

BACKGROUND: The arterial partial pressure of O2 and the fraction of inspired oxygen (PaO2/FiO2) ratio is widely used in ICUs as an indicator of oxygenation status. Although cardiac surgery and ICU scores can predict mortality, during the first hours after cardiac surgery few instruments are available to assess outcome. The aim of this study was to evaluate the usefulness of PaO2/FIO2 ratio to predict mortality in patients immediately after cardiac surgery. METHODS: We prospectively studied 2725 consecutive cardiac surgery patients between 2004 and 2009. PaO2/FiO2 ratio was measured on admission and at 3 h, 6 h, 12 h and 24 h after ICU admission, together with clinical data and outcomes. RESULTS: All PaO2/FIO2 ratio measurements differed between survivors and non-survivors (p < 0.001). The PaO2/FIO2 at 3 h after ICU admission was the best predictor of mortality based on area under the curve (p < 0.001) and the optimum threshold estimation gave an optimal cut-off of 222 (95% Confidence interval (CI): 202-242), yielding three groups of patients: Group 1, with PaO2/FIO2 > 242; Group 2, with PaO2/FIO2 from 202 to 242; and Group 3, with PaO2/FIO2 < 202. Group 3 showed higher in-ICU mortality and ICU length of stay and Groups 2 and 3 also showed higher respiratory complication rates. The presence of a PaO2/FIO2 ratio < 202 at 3 h after admission was shown to be a predictor of in-ICU mortality (OR:1.364; 95% CI:1.212-1.625, p < 0.001) and of worse long-term survival (88.8% vs. 95.8%; Log rank p = 0.002. Adjusted Hazard ratio: 1.48; 95% CI:1.293-1.786; p = 0.004). CONCLUSIONS: A simple determination of PaO2/FIO2 at 3 h after ICU admission may be useful to identify patients at risk immediately after cardiac surgery.

Optimum threshold estimation based on cost function in a multistate diagnostic setting.

In the diagnostic area, the usual setting considers two populations: nondiseased and diseased. The use of the standard ROC analysis methodology is well established. Sometimes, however, diagnostic problems inherently include more than two classification states. For example, 'yes, uncertain, no' or 'low, normal, high'. Here we consider a three-normal distribution setting and derive estimators for the optimum thresholds between states based on a cost function. These estimators can be extended for clinical contexts with more than three states. This approach is well known for the two-state setting and its advantage lies in the fact that it accounts for the specific context's properties, such as disease prevalence and classification costs. Here we calculated the variance of the estimators by the use of parametric methods on nonlinear equations and we constructed confidence intervals accounting for possible uncertainty in the threshold estimation. We conducted a simulation study to assess the performance of these estimators and the confidence intervals. Comparisons with the naive threshold estimation method of joining the distributions two-by-two and applying standard ROC techniques proved that the latter method is not reliable for all parameter combinations and should be avoided.

Estimation of the diagnostic threshold accounting for decision costs and sampling uncertainty.

Medical diagnostic tests are used to classify subjects as non-diseased or diseased. The classification rule usually consists of classifying subjects using the values of a continuous marker that is dichotomised by means of a threshold. Here, the optimum threshold estimate is found by minimising a cost function that accounts for both decision costs and sampling uncertainty. The cost function is optimised either analytically in a normal distribution setting or empirically in a free-distribution setting when the underlying probability distributions of diseased and non-diseased subjects are unknown. Inference of the threshold estimates is based on approximate analytically standard errors and bootstrap-based approaches. The performance of the proposed methodology is assessed by means of a simulation study, and the sample size required for a given confidence interval precision and sample size ratio is also calculated. Finally, a case example based on previously published data concerning the diagnosis of Alzheimer's patients is provided in order to illustrate the procedure.