Ji Lin

Bio: Ji Lin is an academic researcher. The author has contributed to research in topics: Event (probability theory) & Uniformly most powerful test. The author has an hindex of 3, co-authored 3 publications receiving 51 citations.

Alternative Analysis Methods for Time to Event Endpoints Under Nonproportional Hazards: A Comparative Analysis

Abstract: The log-rank test is most powerful under proportional hazards (PH). In practice, non-PH patterns are often observed in clinical trials, such as in immuno-oncology; therefore, alternative methods ar...

Alternative Analysis Methods for Time to Event Endpoints under Non-proportional Hazards: A Comparative Analysis

Abstract: The log-rank test is most powerful under proportional hazards (PH). In practice, non-PH patterns are often observed in clinical trials, such as in immuno-oncology; therefore, alternative methods are needed to restore the efficiency of statistical testing. Three categories of testing methods were evaluated, including weighted log-rank tests, Kaplan-Meier curve-based tests (including weighted Kaplan-Meier and Restricted Mean Survival Time, RMST), and combination tests (including Breslow test, Lee's combo test, and MaxCombo test). Nine scenarios representing the PH and various non-PH patterns were simulated. The power, type I error, and effect estimates of each method were compared. In general, all tests control type I error well. There is not a single most powerful test across all scenarios. In the absence of prior knowledge regarding the PH or non-PH patterns, the MaxCombo test is relatively robust across patterns. Since the treatment effect changes overtime under non-PH, the overall profile of the treatment effect may not be represented comprehensively based on a single measure. Thus, multiple measures of the treatment effect should be pre-specified as sensitivity analyses to evaluate the totality of the data.

Rejoinder to Letter to the Editor "The Hazards of Period Specific and Weighted Hazard Ratios".

Abstract: We would like to thank the authors of the letter (Bartlett et al. 2020) for sharing their concerns regarding reporting treatment effect under nonproportional hazards (NPH), and we respect their pos...

Durvalumab alone and durvalumab plus tremelimumab versus chemotherapy in previously untreated patients with unresectable, locally advanced or metastatic urothelial carcinoma (DANUBE): a randomised, open-label, multicentre, phase 3 trial

Abstract: Background: Survival outcomes are poor for patients with metastatic urothelial carcinoma who receive standard, first-line, platinum-based chemotherapy. We assessed the overall survival of patients who received durvalumab (a PD-L1 inhibitor), with or without tremelimumab (a CTLA-4 inhibitor), as a first-line treatment for metastatic urothelial carcinoma. Methods: DANUBE is an open-label, randomised, controlled, phase 3 trial in patients with untreated, unresectable, locally advanced or metastatic urothelial carcinoma, conducted at 224 academic research centres, hospitals, and oncology clinics in 23 countries. Eligible patients were aged 18 years or older with an Eastern Cooperative Oncology Group performance status of 0 or 1. We randomly assigned patients (1:1:1) to receive durvalumab monotherapy (1500 mg) administered intravenously every 4 weeks; durvalumab (1500 mg) plus tremelimumab (75 mg) administered intravenously every 4 weeks for up to four doses, followed by durvalumab maintenance (1500 mg) every 4 weeks; or standard-of-care chemotherapy (gemcitabine plus cisplatin or gemcitabine plus carboplatin, depending on cisplatin eligibility) administered intravenously for up to six cycles. Randomisation was done through an interactive voice–web response system, with stratification by cisplatin eligibility, PD-L1 status, and presence or absence of liver metastases, lung metastases, or both. The coprimary endpoints were overall survival compared between the durvalumab monotherapy versus chemotherapy groups in the population of patients with high PD-L1 expression (the high PD-L1 population) and between the durvalumab plus tremelimumab versus chemotherapy groups in the intention-to-treat population (all randomly assigned patients). The study has completed enrolment and the final analysis of overall survival is reported. The trial is registered with ClinicalTrials.gov, NCT02516241, and the EU Clinical Trials Register, EudraCT number 2015-001633-24. Findings: Between Nov 24, 2015, and March 21, 2017, we randomly assigned 1032 patients to receive durvalumab (n=346), durvalumab plus tremelimumab (n=342), or chemotherapy (n=344). At data cutoff (Jan 27, 2020), median follow-up for survival was 41·2 months (IQR 37·9–43·2) for all patients. In the high PD-L1 population, median overall survival was 14·4 months (95% CI 10·4–17·3) in the durvalumab monotherapy group (n=209) versus 12·1 months (10·4–15·0) in the chemotherapy group (n=207; hazard ratio 0·89, 95% CI 0·71–1·11; p=0·30). In the intention-to-treat population, median overall survival was 15·1 months (13·1–18·0) in the durvalumab plus tremelimumab group versus 12·1 months (10·9–14·0) in the chemotherapy group (0·85, 95% CI 0·72–1·02; p=0·075). In the safety population, grade 3 or 4 treatment-related adverse events occurred in 47 (14%) of 345 patients in the durvalumab group, 93 (27%) of 340 patients in the durvalumab plus tremelimumab group, and in 188 (60%) of 313 patients in the chemotherapy group. The most common grade 3 or 4 treatment-related adverse event was increased lipase in the durvalumab group (seven [2%] of 345 patients) and in the durvalumab plus tremelimumab group (16 [5%] of 340 patients), and neutropenia in the chemotherapy group (66 [21%] of 313 patients). Serious treatment-related adverse events occurred in 30 (9%) of 345 patients in the durvalumab group, 78 (23%) of 340 patients in the durvalumab plus tremelimumab group, and 50 (16%) of 313 patients in the chemotherapy group. Deaths due to study drug toxicity were reported in two (1%) patients in the durvalumab group (acute hepatic failure and hepatitis), two (1%) patients in the durvalumab plus tremelimumab group (septic shock and pneumonitis), and one (<1%) patient in the chemotherapy group (acute kidney injury). Interpretation: This study did not meet either of its coprimary endpoints. Further research to identify the patients with previously untreated metastatic urothelial carcinoma who benefit from treatment with immune checkpoint inhibitors, either alone or in combination regimens, is warranted. Funding: AstraZeneca.

Robust Design and Analysis of Clinical Trials With Nonproportional Hazards: A Straw Man Guidance From a Cross-Pharma Working Group

Abstract: Loss of power and clear description of treatment differences are key issues in designing and analyzing a clinical trial where nonproportional hazard (NPH) is a possibility. A log-rank test may be i...

Robust Design and Analysis of Clinical Trials With Non-proportional Hazards: A Straw Man Guidance from a Cross-pharma Working Group

Abstract: Loss of power and clear description of treatment differences are key issues in designing and analyzing a clinical trial where non-proportional hazard is a possibility. A log-rank test may be very inefficient and interpretation of the hazard ratio estimated using Cox regression is potentially problematic. In this case, the current ICH E9 (R1) addendum would suggest designing a trial with a clinically relevant estimand, e.g., expected life gain. This approach considers appropriate analysis methods for supporting the chosen estimand. However, such an approach is case specific and may suffer lack of power for important choices of the underlying alternate hypothesis distribution. On the other hand, there may be a desire to have robust power under different deviations from proportional hazards. Also, we would contend that no single number adequately describes treatment effect under non-proportional hazards scenarios. The cross-pharma working group has proposed a combination test to provide robust power under a variety of alternative hypotheses. These can be specified for primary analysis at the design stage and methods appropriately accounting for combination test correlations are efficient for a variety of scenarios. We have provided design and analysis considerations based on a combination test under different non-proportional hazard types and present a straw man proposal for practitioners. The proposals are illustrated with real life example and simulation.

Assessing the Impact of COVID-19 on the Clinical Trial Objective and Analysis of Oncology Clinical Trials—Application of the Estimand Framework

Abstract: Coronavirus disease 2019 (COVID-19) outbreak has rapidly evolved into a global pandemic The impact of COVID-19 on patient journeys in oncology represents a new risk to interpretation of trial resu

The hazards of period specific and weighted hazard ratios

Abstract: How to adequately handle nonproportional hazards (NPH) in clinical trials is an important and timely question, particularly given recent advances in immuno-oncology treatments, in which survival cu...