Background: Pain is a common symptom of hemophilia that may adversely affect patients’ quality of life (QoL). Previous post hoc analyses of prophylaxis with recombinant factor IX Fc fusion protein ...(rFIXFc) have been published for adults and adolescents, demonstrating improvements in health-related QoL (HRQoL) when assessed by the haemophilia-specific QoL (HaemAQoL) questionnaire. Objective: To describe in depth the evolution of QoL, pain- and activity-related domains and questions for pediatric, adolescent, and adult patients with hemophilia B treated with rFIXFc prophylaxis. Design: A post hoc analysis of data from a series of clinical trials. Methods: This post hoc , long-term analysis assessed patient-reported outcomes (PROs) from the Kids B-LONG (NCT01440946: pediatric) and B-LONG (NCT01027364: adults and adolescents) parent studies and the B-YOND (NCT01425723: all age groups) extension study. Results: Ninety-two adult and adolescent patients that started in the B-LONG study were assessed, with a median (range) duration of follow-up of 58.9 (0.0–78.4) months. The Haem-A-QoL total score was significantly reduced from baseline by 4.45 ( p ⩽ 0.01), as were the subdomains ‘physical health’ (9.10; p = 0.001), ‘sports and leisure’ (11.25; p ⩽ 0.01), ‘treatment’ (2.69; p = 0.05), and ‘view of self’ (5.81; p = 0.002). Thirty pediatric patients that started in the Kids B-LONG study were assessed, with a median (min–max) duration of follow-up of 36.7 (9.0–59.9) months. The high level of satisfaction demonstrated by the PROs at baseline was maintained. Conclusion: rFIXFc prophylaxis reduced perceived pain and increased levels of physical activity with sustained, long-term improvements in QoL in adult and adolescent patients with hemophilia B and maintained high QoL scores in pediatric patients.
PurposeThe currently ongoing Epidemiological Strategy and Medical Economics (ESME) research programme aims at centralising real-life data on oncology care for epidemiological research purposes. We ...draw on results from the metastatic breast cancer (MBC) cohort to illustrate the methodology used for data collection in the ESME research programme.ParticipantsAll consecutive ≥18 years patients with MBC treatment initiated between 2008 and 2014 in one of the 18 French Comprehensive Cancer Centres were selected. Diagnostic, therapeutic and follow-up data (demographics, primary tumour, metastatic disease, treatment patterns and vital status) were collected through the course of the disease. Data collection is updated annually.Finding to dateWith a recruitment target of 30 000 patients with MBC by 2019, we currently screened a total of 45 329 patients, and >16 700 patients with a metastatic disease treatment initiated after 2008 have been selected. 20.7% of patients had an hormone receptor (HR)-negative MBC, 73.7% had a HER2-negative MBC and 13.9% were classified as triple-negative BC (ie, HER2 and HR status both negative). Median follow-up duration from MBC diagnosis was 48.55 months for the whole cohort.Future plansThese real-world data will help standardise the management of MBC and improve patient care. A dozen of ancillary research projects have been conducted and some of them are already accepted for publication or ready to be issued. The ESME research programme is expanding to ovarian cancer and advanced/metastatic lung cancer. Our ultimate goal is to achieve a continuous link to the data of the cohort to the French national Health Data System for centralising data on healthcare reimbursement (drugs, medical procedures), inpatient/outpatient stays and visits in primary/secondary care settings.Trial registration number NCT03275311; Pre-results.
The staging of node-negative non–small-cell lung cancer is modified in the 7th edition TNM classification. Here, we pool data from the National Cancer Institute of Canada Clinical Trials Group JBR.10 ...trial and the Cancer and Leukemia Group B-9633 trial to explore the prognostic and predictive effects of the new T-size descriptors and KRAS mutation status.
Node-negative patients were reclassified as T2a (>3–⩽5 cm), T2b (>5–⩽7 cm), T3 (>7 cm) or T ⩽ 3 cm (⩽3 cm, but other T2 characteristics).
Of 538 eligible patients, 288 (53.5%) were T2a, 111 (21%) T2b, 62 (11.5%) T3, whereas 77 (14%) T⩽3 cm were excluded to avoid confounding. KRAS mutations were detected in 104 of 390 patients (27%). T-size was prognostic for disease-free survival (p = 0.03), but borderline for overall survival (OS; p = 0.10), on multivariable analysis. Significant interaction between the prognostic value of KRAS and tumor size was observed for OS (p = 0.01), but not disease-free survival (p = 0.10). There was a nonsignificant trend (p = 0.24) for increased chemotherapy effect on OS with advancing T-size (hazard ratio HR T2a 0.90, 0.63–1.30; T2b 0.69, 0.38–1.24; and T3 0.57, 0.28–1.17). The HR for chemotherapy effect on OS in T2a patients with KRAS wild-type tumors was 0.81 (p = 0.36), whereas a trend for detrimental effect was observed in those with mutant tumors (HR 2.11; p = 0.09; interaction p = 0.05). Similar trends were observed in T2b to T3 patients with wild-type (HR 0.86; p = 0.62), and KRAS mutant tumors (HR 1.16; p = 0.74; interaction p = 0.58).
Chemotherapy effect seems to increase with tumor size. However, this small study could not identify subgroups of patients who did or did not derive significant benefit from adjuvant chemotherapy based on T-size or KRAS status.
Abstract
Background
New rescue regimens are needed for pediatric refractory/recurrent low-grade glioma. Nilotinib is a tyrosine kinase inhibitor that has potential synergistic effects with ...vinblastine on angiogenesis, tumor cell growth, and immunomodulation.
Methods
This phase I trial aimed to determine the recommended doses of this combination for phase II trials (RP2D) using the dual-agent Bayesian continual reassessment method. Nilotinib was given orally twice daily (BID) in combination with once-weekly vinblastine injections for a maximum of 12 cycles of 28 days (clinicaltrials.gov, NCT01884922).
Results
Thirty-five pediatric patients were enrolled across 4 dose levels. The median age was 7 years and 10 had neurofibromatosis type 1. Patients had received a median of 3 prior treatment lines and 25% had received more than 4 previous treatment lines. Dose-limiting toxicity (DLT) during cycle 1 was hematologic, dermatologic, and cardiovascular. The RP2D was identified at 3 mg/m2 weekly for vinblastine with 230 mg/m2 BID for nilotinib (estimated probability of DLT = 18%; 95% credibility interval, 7–29%). Fifteen patients completed the 12 cycles; 2 stopped therapy prematurely due to toxicity and 18 due to disease progression. Three patients achieved a partial response leading to an objective response rate of 8.8% (95% confidence interval CI, 1.9–23.7), and the disease control rate was 85.3% (95% CI, 68.9–95.1). The 12-month progression-free survival was 37.1% (95% CI, 23.2–53.67).
Conclusions
Vinblastine and nilotinib combination was mostly limited by myelosuppression and dermatologic toxicity. The efficacy of the combination at the RP2D is currently evaluated in a randomized phase II trial comparing this regimen to vinblastine alone.
At the end of the dose escalation step of phase I trials in oncology, it is increasingly frequent to include patients in expansion cohorts. However, the objective of the expansion cohorts, the number ...of patients included and their justification are insufficiently explained in the protocols. These cohorts are sometimes of considerable size. The aim of this article is to outline the methodology of expansion cohorts in order to provide recommendations for their planning in practice. This work has been undertaken in collaboration with the statisticians of the early phase investigation centers (CLIP(2)), supported by INCA. First, we have outlined the recent articles published on the expansion cohorts in phase I. We then proposed recommendations, in terms of objectives and number of patients to be included, to guide investigators and facilitate the use of these expansion cohorts in practice. Manji et al. have identified 149 phase I clinical trials using expansion cohorts in oncology with a review of the literature between 2006 and 2011 (Manji et al., 2013). Objectives of the expansion cohort were reported in 111 trials (74%). In these trials, safety was the most reported objective (80% of trials), followed by efficacy (45%). According to this review, the number of patients included in these cohorts was insufficiently justified. This result was confirmed by the study of literature that we conducted over the period 2011-2014. We propose to define the number of patients to be included in expansion cohorts in terms of (1) their objectives, (2) the statistical criteria and (3) the clinical context of the trial. The toxicity study remains the primary objective to evaluate in the expansion phase. In some contexts, the activity study is considered as co-primary objective, either for identifying preliminary signs of activity in studies like screening, or for studying the activity when the target population is known. This study is then considered as phase I/II, and experience plans of phase II can be adapted for planning expansion cohorts. Recommendations for the size of expansion cohorts are proposed. Despite the exploratory character of the expansion cohort, a justification of their size based on assumptions statistically defined is recommended in order to provide an interpretable conclusion and to quantify the risk of errors.
Le but principal d'un essai de phase I en oncologie est d'identifier, parmi un nombre fini de doses, la dose à recommander d'un nouveau traitement pour les évaluations ultérieures, sur un petit ...nombre de patients.Le critère de jugement principal est classiquement la toxicité. Bien que la toxicité soit mesurée pour différents organes sur une échelle gradée, elle est généralement réduite à un indicateur binaire appelé "toxicité dose-limitante" (DLT). Cette simplification très réductrice est problématiqu, en particulier pour les thérapies, dites "thérapies ciblées", associées à peu de DLTs.Dans ce travail, nous proposons un score de toxicité qui résume l'ensemble des toxicités observées chez un patient. Ce score, appelé TTP pour Total Toxicity Profile, est défini par la norme euclidienne des poids associés aux différents types et grades de toxicités possibles. Les poids reflètent l'importance clinique des différentes toxicités.\\ Ensuite, nous proposons la méthode de recherche de dose, QLCRM pour Quasi-Likelihood Continual Reassessment Method, modélisant la relation entre la dose et le score de toxicité TTP à l'aide d'une régression logistique dans un cadre fréquentiste.A l'aide d'une étude de simulation, nous comparons la performance de cette méthode à celle de trois autres approches utilisant un score de toxicité : i) la méthode de Yuan et al. (QCRM) basée sur un modèle empirique pour estimer, dans un cadre bayésien, la relation entre la dose et le score, ii) la méthode d'Ivanova et Kim (UA) dérivée des méthodes algorithmiques et utilisant une régression isotonique pour estimer la dose à recommander en fin d'essai, iii) la méthode de Chen et al. (EID) basée sur une régression isotonique pour l'escalade de dose et l'identification de la dose à recommander. Nous comparons ensuite ces quatre méthodes utilisant le score de toxicité aux méthodes CRM basées sur le critère binaire DLT. Nous étudions également l'impact de l'erreur de classement des grades pour les différentes méthodes, guidées par le score de toxicité ou par la DLT.Enfin, nous illustrons le processus de construction du score de toxicité ainsi que l'application de la méthode QLCRM dans un essai réel de phase I. Dans cette application, nous avons utilisé une approche Delphi pour déterminer avec les cliniciens la matrice des poids et le score de toxicité jugé acceptable.Les méthodes QLCRM, QCRM, UA et EID présentent une bonne performance en termes de capacité à identifier correctement la dose à recommander et de contrôle du surdosage. Dans un essai incluant 36 patients, le pourcentage de sélection correcte de la dose à recommander obtenu avec les méthodes QLCRM et QCRM varie de 80 à 90% en fonction des situations. Les méthodes basées sur le score TTP sont plus performantes et plus robustes aux erreurs de classement des grades que les méthodes CRM basées sur le critère binaire DLT.Dans l'application rétrospective, le processus de construction du score apparaît faisable facilement. Cette étude nous a conduits à proposer des recommandations pour guider les investigateurs et faciliter l'utilisation de cette approche dans la pratique.En conclusion, la méthode QLCRM prenant en compte l'ensemble des toxicités s'avère séduisante pour les essais de phase I évaluant des médicaments associés à peu de DLTs a priori, mais avec des toxicités multiples modérées probables.
The aim of a phase I oncology trial is to identify a dose with an acceptable safety level. Most phase I designs use the Dose-Limiting Toxicity (DLT), a binary endpoint, to assess the level of toxicity. DLT might be an incomplete endpoint for investigating molecularly targeted therapies as a lot of useful toxicity information is discarded.In this work, we propose a quasi-continuous toxicity score, the Total Toxicity Profile (TTP), to measure quantitatively and comprehensively the overall burden of multiple toxicities. The TTP is defined as the Euclidean norm of the weights of toxicities experienced by a patient, where the weights reflect the relative clinical importance of each type and grade of toxicity.We propose then a dose-finding design, the Quasi-Likelihood Continual Reassessment Method (QLCRM), incorporating the TTP-score into the CRM, with a logistic model for the dose-toxicity relationship in a frequentist framework. Using simulations, we compare our design to three existing designs for quasi-continuous toxicity scores: i) the QCRM design, proposed by Yuan et al., with an empiric model for the dose-toxicity relationship in a Bayesian framework, ii) the UA design of Ivanova and Kim derived from the "up-and-down" methods for the dose-escalation process and using an isotonic regression to estimate the recommended dose at the end of the trial, and iii) the EID design of Chen et al. using the isotonic regression for the dose-escalation process and for the identification of the recommended dose.We also perform a simulation study to evaluate the TTP-driven methods in comparison to the classical DLT-driven CRM. We then evaluate the robustness of these designs in a setting where grades can be misclassified.In the last part of this work, we illustrate the process of building the TTP-score and the application of the QLCRM method through the example of a paediatric trial. In this study, we have used the Delphi method to elicit the weights and the target toxicity-score considered as an acceptable toxicity measure.All designs using the TTP-score to identify the recommended dose had good performance characteristics for most scenarios, with good overdosing control. For a sample size of 36, the percentage of correct selection for the QLCRM ranged from 80 to 90%, with similar results for the QCRM design. Simulation study demonstrates also that score-driven designs present an improved performance and robustness compared to conventional DLT-driven designs. In the retrospective application of erlotinib trial, the consensus weights as well as the target-TTP were easily obtained, confirming the feasibility of the process. Some guidelines to facilitate the process in a real clinical trial for a better practice of this approach are suggested.The QLCRM method based on the TTP-endpoint combining multiple graded toxicities is an appealing alternative to the conventional dose-finding designs, especially in the context of molecularly targeted agents.
Le but principal d'un essai de phase I en oncologie est d'identifier, parmi un nombre fini de doses, la dose à recommander d'un nouveau traitement pour les évaluations ultérieures, sur un petit ...nombre de patients.Le critère de jugement principal est classiquement la toxicité. Bien que la toxicité soit mesurée pour différents organes sur une échelle gradée, elle est généralement réduite à un indicateur binaire appelé "toxicité dose-limitante" (DLT). Cette simplification très réductrice est problématiqu, en particulier pour les thérapies, dites "thérapies ciblées", associées à peu de DLTs.Dans ce travail, nous proposons un score de toxicité qui résume l'ensemble des toxicités observées chez un patient. Ce score, appelé TTP pour Total Toxicity Profile, est défini par la norme euclidienne des poids associés aux différents types et grades de toxicités possibles. Les poids reflètent l'importance clinique des différentes toxicités.\\ Ensuite, nous proposons la méthode de recherche de dose, QLCRM pour Quasi-Likelihood Continual Reassessment Method, modélisant la relation entre la dose et le score de toxicité TTP à l'aide d'une régression logistique dans un cadre fréquentiste.A l'aide d'une étude de simulation, nous comparons la performance de cette méthode à celle de trois autres approches utilisant un score de toxicité : i) la méthode de Yuan et al. (QCRM) basée sur un modèle empirique pour estimer, dans un cadre bayésien, la relation entre la dose et le score, ii) la méthode d'Ivanova et Kim (UA) dérivée des méthodes algorithmiques et utilisant une régression isotonique pour estimer la dose à recommander en fin d'essai, iii) la méthode de Chen et al. (EID) basée sur une régression isotonique pour l'escalade de dose et l'identification de la dose à recommander. Nous comparons ensuite ces quatre méthodes utilisant le score de toxicité aux méthodes CRM basées sur le critère binaire DLT. Nous étudions également l'impact de l'erreur de classement des grades pour les différentes méthodes, guidées par le score de toxicité ou par la DLT.Enfin, nous illustrons le processus de construction du score de toxicité ainsi que l'application de la méthode QLCRM dans un essai réel de phase I. Dans cette application, nous avons utilisé une approche Delphi pour déterminer avec les cliniciens la matrice des poids et le score de toxicité jugé acceptable.Les méthodes QLCRM, QCRM, UA et EID présentent une bonne performance en termes de capacité à identifier correctement la dose à recommander et de contrôle du surdosage. Dans un essai incluant 36 patients, le pourcentage de sélection correcte de la dose à recommander obtenu avec les méthodes QLCRM et QCRM varie de 80 à 90% en fonction des situations. Les méthodes basées sur le score TTP sont plus performantes et plus robustes aux erreurs de classement des grades que les méthodes CRM basées sur le critère binaire DLT.Dans l'application rétrospective, le processus de construction du score apparaît faisable facilement. Cette étude nous a conduits à proposer des recommandations pour guider les investigateurs et faciliter l'utilisation de cette approche dans la pratique.En conclusion, la méthode QLCRM prenant en compte l'ensemble des toxicités s'avère séduisante pour les essais de phase I évaluant des médicaments associés à peu de DLTs a priori, mais avec des toxicités multiples modérées probables.
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