Beyond maximum grade: modernising the assessment and reporting of adverse events in haematological malignancies

Abstract

Tremendous progress in treatment and outcomes has been achieved across the whole range of haematological malignancies in the past two decades. Although cure rates for aggressive malignancies have increased, nowhere has progress been more impactful than in the management of typically incurable forms of haematological cancer. Population-based data have shown that 5-year survival for patients with chronic myelogenous and chronic lymphocytic leukaemia, indolent B-cell lymphomas, and multiple myeloma has improved markedly. This improvement is a result of substantial changes in disease management strategies in these malignancies. Several haematological malignancies are now chronic diseases that are treated with continuously administered therapies that have unique side-effects over time. In this Commission, an international panel of clinicians, clinical investigators, methodologists, regulators, and patient advocates representing a broad range of academic and clinical cancer expertise examine adverse events in haematological malignancies. The issues pertaining to assessment of adverse events examined here are relevant to a range of malignancies and have been, to date, underexplored in the context of haematology. The aim of this Commission is to improve toxicity assessment in clinical trials in haematological malignancies by critically examining the current process of adverse event assessment, highlighting the need to incorporate patient-reported outcomes, addressing issues unique to stem-cell transplantation and survivorship, appraising challenges in regulatory approval, and evaluating toxicity in real-world patients. We have identified a range of priority issues in these areas and defined potential solutions to challenges associated with adverse event assessment in the current treatment landscape of haematological malignancies.

Figure 1.

Evolution of Therapy in Haematologic Malignancies: Lymphoma as an example of shifting treatment strategies

Figure 2.. Graphical representations and analysis of AEs by the NCI Web Reporting Tool

Characterization and graphical display of Treatment Emergent Adverse Events (TEAEs) from the NCI Web Reporting System. (A) Pie graph of all TEAEs in patients on a Vascular Endothelial Growth Factor Receptor inhibitor (VEGFR2i) and a DNA Repair inhibitor (DNARi). (B) Risk-based monitoring of Diarrhea (dark blue) and Hypertension (light blue) in patients in a clinical trial of a VEGFR2i and a DNARi evaluating AE density by course using an area under the curve approach in a single clinical trial of this combination therapy. (C) Hypertension in patients across 5 clinical trials with VEGFR2i evaluated by grade, course number and number of TEAEs using a contour map. Below is graph that depicts the number of patients at risk by course. (D) Hypertension TEAEs in patients given a VEGFR2i in a clinical trial evaluated by grade, course number and number of TEAEs using a contour map. Below is a graph that depicts the number of patients at risk by course

Figure 3.. Time to event analyses for adverse events per the Toxicity over Time (ToxT) package

(A) Time to grade 2 or worse diarrhea in patients given FOLFOX and IROX in Alliance/NCCTG N9741 and (B) Median time to first occurrence and worst grade toxic effects in patients on the IROX arm only. Adapted with permission from Thanarajasingam et al, Lancet Oncology 2016; 17: 663–70.

Figure 4. ToxT AUC analysis to compare adverse events over time – conceptual and applied

(A) Conceptual example of AUC analysis with patient B demonstrating continuous grade 2 AE and having a higher AUC than patient A with an isolated grade 3 event. (B) Application of AUC analysis depicting mean diarrhea grade over time in patients given FOLFOX and IROX in clinical trial Alliance/NCCTG N9741. Adapted with permission from Thanarajasingam et al, Lancet Oncology 2016; 17: 663–70.

Figure 5.

Relevance of AE Time Profile

Figure 6.

Safety and the Patient Experience Inform Tolerability.

Figure 7A and 7B.

Cause of Death After HCT.

Figure 8.

Cause-specific mortality in adults diagnosed with Hodgkin lymphoma. (Ng Blood 2014 https://doi.org/10.1182/blood-2014-05-579193)

Figure 9.. Weighing Safety and Efficacy in New Drugs.

Rigorous clinical trials allow for a measure of certainty about the data collected in a selected sample of the general population who will eventually use the therapy. The limited scope of these data at the time of marketing approval necessarily abbreviates the information upon which a regulatory decision must be made. Product regulation does not end at marketing approval, and technology is providing us with unprecedented opportunities to learn about safety and effectiveness from a greater variety of patients in the post-marketing setting using different data-capture platforms. These data are most often from uncontrolled settings and present a trade-off between large amounts of data in “real-world” populations on one hand, with challenges in data quality on the other. Reproduced with permission, Sean Khozin, Case Sudies: Data Collection and Application of RWE, Friends of Cancer Research Blueprint for Breakthrough Forum, June 16, 2016. https://www.focr.org/sites/default/files/pdf/Blueprint2016%20-%20Panel1.pdf

Figure 10:. Optimizing Databases for Real World Toxicity Evaluation

Optimizing databases for future toxicity studies with integration of genomic data and clinical data (blue boxes), real time toxicity data provided by health care professionals (green boxes), and patient related outcome measures (yellow boxes)