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Traditional methods of reporting adverse events in clinical trials are inadequate for modern cancer treatments with chronic administration. Conventional analysis and display of maximum grade adverse events do not capture toxicity profiles that evolve over time or longer lasting, lower grade toxic effects; we aimed to address this shortcoming in this study. We developed an analytic approach and standardised, comprehensive format, the Toxicity over Time (ToxT) approach, which combines graphs and adverse event tabular displays with multiple longitudinal statistical techniques into a readily applicable method to study toxic effects. Plots visualising summary statistics or individual patient data over discrete timepoints were combined with statistical methods including the following longitudinal techniques: repeated measures models that describe the changes in adverse events across all cycles of treatment; time-to-event analyses of first and worst grade toxicity; and area under the curve (AUC) analyses summarising adverse event profiles over the entire course of a study, including chronic low-grade events. We applied ToxT analysis to adverse event data from two completed North Central Cancer Treatment Group (NCCTG/Alliance) trials: N9741 (NCT00003594), in which different combinations of oxaliplatin, 5-fluorouracil, and irinotecan were investigated for metastatic colorectal cancer, and 979254, in which survivors of breast cancer were given venlafaxine or placebo for control of hot flashes. In trial NCCTG 979254 there was a higher incidence of late-occurring dry mouth in patients who were given venlafaxine than in those given placebo (week 1 [baseline]: 13% [six incidence in 48 patients, SD 5] vs 22% [11/49, SD 6]; p=0·20; week 5: 49% [24/49, 7] vs 2% [1/46, 2]; p<0·0001). In trial NCCTG N9741 there was an increased incidence of early nausea for patients given irinotecan plus oxaliplatin (IROX) compared with those given 5-fluorouracil plus oxaliplatin (FOLFOX; cycle 1 mean grade nausea 1·1 [SD 1·0] vs 0·6 [0·7]; p<0·0001). Event charts showed earlier occurrences of higher grades of diarrhoea for patients given IROX compared with those given FOLFOX, and the AUC analysis shows a higher magnitude of diarrhoea consistently over time throughout the study in patients given IROX versus those given FOLFOX (mean AUC 4·2 [SD 5·2] vs 2·9 [4·2]; p<0·0001). The ToxT analytical approach incorporates the dimension of time into adverse event assessment and offers a more comprehensive depiction of toxic effects than present methods. With new, continuously administered targeted agents, immunotherapy, and maintenance regimens, these improved longitudinal analyses are directly relevant to patients and are crucial in cancer clinical trials. National Cancer Institute of the National Institutes of Health and the Mayo Comprehensive Cancer Center.

Peripheral T-cell lymphomas (PTCL), a heterogeneous group of mature aggressive non-Hodgkin’s lymphomas, carry a worse prognosis for most subtypes when compared with their B-cell counterparts. Despite recent approval of newer therapies, the outlook for patients with relapsed/refractory (RR) PTCL remains poor and new treatment strategies are clearly needed. Targeting the profoundly immunosuppressive tumor microenvironment in PTCL is one such approach. To determine whether immune checkpoint blockade targeting program death receptor 1 would be effective in PTCL, we conducted an investigator-initiated phase 2 prospective study of single-agent nivolumab for RR PTCL. We report here results of the pre-specified interim analysis.MethodsThe primary objective was to assess the overall response rate (ORR). Secondary objectives were to assess safety and tolerability of nivolumab in PTCL and to assess progression-free survival (PFS), duration of response (DOR) and overall survival (OS). Hyperprogressive disease (HPD) was defined as time-to-treatment failure of less than or equal to one month from initiation of therapy.ResultsTwelve patients who received at least one cycle of nivolumab were included in this interim analysis. Half (6/12) of the patients had angioimmunoblastic T-cell lymphoma (AITL), 3/12 had PTCL, not otherwise specified. Most (11/12) were advanced stage, had extranodal disease (97.1%) and had received a prior autologous stem cell transplant (50%). The ORR was 33% (95% CI: 12.3 to 63.7%) with two complete response and two partial response. The median PFS was however short at 2.7 months (95% CI: 1.5 to NE); and the median OS was 6.7 months (95% CI: 3.4 to NE). The median DOR was also short at 3.6 months (95% CI: 1.9 to NE). HPD occurred in four patients, three of whom had AITL. Observed grade 3 and higher adverse events (AEs) were non-hematologic in 5/12 (42%), while hematologic AEs were seen in 3/12 (25%).ConclusionsNivolumab had modest clinical activity in R/R PTCL. Due to a high number of hyperprogression and short DOR, a decision was made to halt the study. These findings likely reflect the distinct biology of PTCL and should be considered when designing future studies using checkpoint inhibitors in these diseases.Trial registration numberNCT03075553.

Background The US Food and Drug Administration (FDA) released a draft guidance document detailing core patient-reported outcomes in cancer clinical trials, including physical function (PF). The objectives of this study were to develop analytic methods and visualizations of patient-reported PF in patients with cancer. Methods We applied an estimand framework to a patient-reported tolerability endpoint to develop data summaries cross-sectionally and over time, along with visualizations. We accomplished this through iterative feedback with clinicians, statisticians, and FDA stakeholders using three clinical trial datasets in hematologic malignancies. Graphical approaches were applied to three datasets in hematologic malignancies: (1) patients with myeloproliferative neoplasms enrolled in MPN-RC 111/112 trials completed EORTC QLQ-C30 over 12 months; (2) patients with hematologic malignancies undergoing CAR-T cell therapy or autologous transplant who completed FACT questionnaires over 6 months; and (3) patients with multiple myeloma or amyloidosis who completed the PROMIS-29 questionnaire over 6 months. Zoom polls were administered to two stakeholder groups (clinicians/clinical investigators and patient advocates) to elicit feedback. Results Visualizations included stacked bar charts, line plots of arithmetic mean changes from baseline, pie charts, waffle plots, and waterfall plots of PF data. Graphics considered scaled scores and individual items and included delineation of PRO completion rate at each time point. Confidence intervals and reference lines were included as applicable, and colorblind accessible colors were implemented to ensure inclusivity of all visualizations. Data summaries over time reporting “worst” change were difficult to interpret. In terms of stakeholders’ preference, patients preferred stacked bar charts while clinicians equally favored stacked bar charts and line plots; both patients and clinicians preferred waterfall plots to pie charts. Patient feedback highlighted the need for various graphics to convey group level trends and granular individual-patient level information. Conclusion Patient-reported PF informs the evaluation of treatment tolerability in cancer trials. Data summaries and visualizations of physical function developed through an iterative process were reviewed favorably by patients, clinicians and FDA stakeholders in this study. Future work to systematically assess accuracy of interpretation of the various analytic and visualization methods is a necessary next step across clinical, regulatory, payer and patient stakeholders. Trial registration NCT01259817, NCT01259856.

Purpose Missing scores complicate analysis of the Patient-Reported Outcomes version of the Common Terminology Criteria for Adverse Events (PRO-CTCAE) because patients with and without missing scores may systematically differ. We focus on optimal analysis methods for incomplete PRO-CTCAE items, with application to two randomized, double-blind, placebo-controlled, phase III trials. Methods In Alliance A091105 and COMET-2, patients completed PRO-CTCAE items before randomization and several times post-randomization ( N  = 64 and 107, respectively). For each trial, we conducted between-arm comparisons on the PRO-CTCAE via complete-case two-sample t -tests, mixed modeling with contrast, and multiple imputation followed by two-sample t -tests. Because interest lies in whether CTCAE grades can inform missing PRO-CTCAE scores, we performed multiple imputation with and without CTCAE grades as auxiliary variables to assess the added benefit of including them in the imputation model relative to only including PRO-CTCAE scores across all cycles. Results PRO-CTCAE completion rates ranged from 100.0 to 71.4% and 100.0 to 77.1% across time in A091105 and COMET-2, respectively. In both trials, mixed modeling and multiple imputation provided the most similar estimates of the average treatment effects. Including CTCAE grades in the imputation model did not consistently narrow confidence intervals of the average treatment effects because correlations for the same PRO-CTCAE item between different cycles were generally stronger than correlations between each PRO-CTCAE item and its corresponding CTCAE grade at the same cycle. Conclusion For between-arm comparisons, mixed modeling and multiple imputation are informative techniques for handling missing PRO-CTCAE scores. CTCAE grades do not provide added benefit for informing missing PRO-CTCAE scores. ClinicalTrials.gov Identifiers: NCT02066181 (Alliance A091105); NCT01522443 (COMET-2).

Background: The PRO-CTCAE provides patient-reported data on symptomatic AEs. A summary metric—the ACS—reflecting total AE burden can be calculated by averaging AE-level composite scores at a given timepoint for each participant. This study investigated the psychometric properties and interpretability of this PRO-CTCAE ACS in patients with breast, lung, or head/neck cancers. Methods: We conducted a secondary analysis of a PRO-CTCAE validation dataset comprising 940 adults undergoing chemotherapy or radiation therapy (clinicaltrials.gov: NCT02158637). We focused on empirically recommended symptom terms for three cancer sites. Analyses included Spearman’s correlations, coefficient alpha, and eigenvalues from the correlation matrices, confirmatory factor analysis (CFA), and principal component analysis (PCA). Latent profile analysis (LPA) was used to assess ACS interpretability in the lung cohort. Results: Mean composite score inter-correlations were moderate (0.30–0.35), and coefficient alphas were high (0.81–0.91). Eigenvalue ratios and CFA supported retention of a single factor/component, with suitable model fit indices. ACS correlated highly with factor scores and the first principal component from the PCA. Reduced sets of terms produced reliable scores that closely approximated the full set scores and aligned with external criteria. LPA in the lung subgroup identified four latent classes; ACS differentiated high vs. low symptom burden groups but did not distinguish the two groups expressing distinct symptom profiles. Conclusion: The ACS demonstrated structural validity through adequately fitting linear factor models and effectively summarized symptomatic AE burden. However, similar ACS values may mask clinically distinct symptomatic AE profiles, underscoring the value of both summary metrics and profile-based approaches.

There are many relevant stakeholders with an interest in safety reporting, and diverging perceptions of importance can create tensions between patients, clinicians, investigators, commercial sponsors, and regulatory authorities.4 Clinical research, including interventional clinical trials (CTs), is a key factor in ensuring patient safety through establishing evidence-based treatments that truly benefit patients. Drawing on our growing knowledge of the toxicity patterns associated with novel therapies, the authors additionally propose a practical framework to enhance the evaluation, reporting, and interpretation of treatment tolerability in the context of targeted and immunotherapies.9 Thereby, the TLH AE Commission aims to put patients first and outlines pragmatic steps to revise our approach to measuring tolerability, a construct that reflects how patients feel and function on treatment. Striving for health equity on a global scale, there remain substantial challenges in low- and middle-income countries which may be addressed through infrastructure development, human resources training including integration of ancillary specialists and adaptation of global guidelines to local realities.10 REDUCING BUREAUCRACY IN CLINICAL TRIALS The coalition for reducing bureaucracy in clinical trials (RBinCT) is a cross-disciplinary coalition of medical societies and patient advocates, where EHA has played a central role in fostering alignment between stakeholders.11 The RBinCT campaign has advocated for substantial changes in safety reporting. The “triangle of patient reality” links toxicity, quality of life, and patient preferences to guide research and clinical decisions.

IntroductionAccurate, patient-centred evaluation of physical function in patients with cancer can provide important information on the functional impacts experienced by patients both from the disease and its treatment. Increasingly, digital health technology is facilitating and providing new ways to measure symptoms and function. There is a need to characterise the longitudinal measurement characteristics of physical function assessments, including clinician-reported outcome, patient-reported ported outcome (PRO), performance outcome tests and wearable data, to inform regulatory and clinical decision-making in cancer clinical trials and oncology practice.Methods and analysisIn this prospective study, we are enrolling 200 English-speaking and/or Spanish-speaking patients with breast cancer or lymphoma seen at Mayo Clinic or Yale University who will receive intravenous cytotoxic chemotherapy. Physical function assessments will be obtained longitudinally using multiple assessment modalities. Participants will be followed for 9 months using a patient-centred health data aggregating platform that consolidates study questionnaires, electronic health record data, and activity and sleep data from a wearable sensor. Data analysis will focus on understanding variability, sensitivity and meaningful changes across the included physical function assessments and evaluating their relationship to key clinical outcomes. Additionally, the feasibility of multimodal physical function data collection in real-world patients with breast cancer or lymphoma will be assessed, as will patient impressions of the usability and acceptability of the wearable sensor, data aggregation platform and PROs.Ethics and disseminationThis study has received approval from IRBs at Mayo Clinic, Yale University and the US Food and Drug Administration. Results will be made available to participants, funders, the research community and the public.Trial registration numberNCT05214144; Pre-results.

Adolescents and young adults (AYA) with lymphoma experience treatment‐related effects in the short and long term that impact their quality of life and survivorship experience. The effort to improve outcomes for AYA lymphoma survivors requires understanding the available literature, identifying current knowledge deficits, designing better clinical trials incorporating the patient perspective, using novel tools to bridge data gaps and building survivorship guidelines that translate research to clinical practice. This review article summarizes the current state of lymphoma treatment‐related outcomes in AYAs and provides future direction.