Initial management strategies for follicular lymphoma

Efficacy and safety of rituximab biosimilars or reference product as first-line treatment in patients with low-tumour-burden follicular lymphoma: A systematic review and meta-analysis

WHAT IS KNOWN AND OBJECTIVE

The role of rituximab in the first-line treatment of low-tumour-burden follicular lymphoma (LTB-FL) has been supported by a large number of data. However, whether rituximab biosimilars have the same efficacy and safety as the reference drug (MabThera) is still controversial.

METHODS

Electronic databases and the ClinicalTrail.gov website were extensively searched using relevant search criteria. The risk of bias of the included studies was assessed using the RoB 2 assessment scale, and the RevMan 5.4 statistical software was used for meta-analysis.

RESULTS AND DISCUSSION

A total of 1223 patients were included in four clinical randomized controlled trials. There was no statistical difference in efficacy between biosimilars and MabThera groups (the objective response rate: RR = 1.00, 95% CI: 0.93-1.08, p = 0.92; the progression-free survival: RR = 1.04, 95% CI: 0.96-1.12, p = 0.30; the overall survival: RR = 1.00, 95% CI: 0.98-1.03, p = 0.76; the serious adverse events: RR = 1.15, 95% CI: 0.69-1.89, p = 0.59; the infusion-related reaction: RR = 0.91, 95% CI: 0.77-1.09, p = 0.32). In terms of safety, there was also no significant difference between two groups.

WHAT IS NEW AND CONCLUSION

Our study concluded that the efficacy and safety of rituximab biosimilars in the treatment of LTB-FL are highly similar to those of the original drug.

Efficacy and Safety of ABP 798: Results from the JASMINE Trial in Patients with Follicular Lymphoma in Comparison with Rituximab Reference Product

Introduction

ABP 798 is being developed as a biosimilar to rituximab reference product (RP), a CD20-directed cytolytic antibody that is approved in the US and EU for the treatment of non-Hodgkin lymphoma (NHL).

Methods

This randomized, double-blind, comparative clinical study (JASMINE) evaluated the efficacy and safety of ABP 798 compared with rituximab RP. Adult, anti-CD20 treatment naïve patients diagnosed with grade 1, 2, or 3a follicular B-cell NHL expressing CD20 were randomized 1:1 to receive a 375 mg/m² infusion of either ABP 798 or rituximab RP once weekly for 4 weeks and at weeks 12 and 20. Tumor assessments were performed at baseline and weeks 12 and 28. Primary endpoint was the risk difference (RD) of overall response rate (ORR) of complete response, unconfirmed complete response, or partial response by week 28 based on data from central, independent, and blinded assessments of disease.

Results

Of the 256 randomized patients, 254 were treated with ABP 798 (n = 128; 100%) or rituximab RP (n = 126; 98.4%); 96 (78.0%) patients in the ABP 798 group and 87 (70.2%) in the rituximab RP group had a best ORR by week 28. The point estimate of RD in ORR between ABP 798 and rituximab RP from the adjusted generalized linear model for stratification factors was 7.7%. Clinical equivalence was based on sequential testing of the one-sided 95% lower confidence limits and one-sided 95% upper confidence limits of RD in ORR (− 1.4% and 16.8%, respectively) which was within the prespecified non-inferiority margin (− 15%) and non-superiority margin (35.5%), respectively. Results of sensitivity analyses were consistent with the primary efficacy analysis. ABP 798 was also comparable to rituximab RP across additional secondary endpoints, further supporting the conclusion of similarity, and including: RD of ORR at week 12; trough serum concentrations; percent of patients with complete depletion of CD19+ cell count at day 8; safety; and immunogenicity.

Conclusions

These results support a conclusion of similar clinical efficacy between ABP 798 and rituximab RP in patients with follicular lymphoma.

NCT Number

NCT02747043; first posted April 21, 2016.

EudraCT Number

2013-005,542-11; submitted 14 October, 2014.

Oral Lichenoid Reaction: An Uncommon Side Effect of Rituximab

Oral lichenoid reactions (OLR) can be caused by systemic drug exposure. To the best of our knowledge, this is the second report describing a case of OLR induced by rituximab administration in a patient with a diagnosis of non-Hodgkin B-cell lymphoma. After 5 doses of rituximab, a typical pattern of OLP was identified with bilateral and symmetrical lesions on the buccal mucosa and on the right lingual margin. This temporal relationship suggested a probable association between oral lesions and drug therapy. The clinical diagnosis of a rituximab-induced OLR was confirmed by an incisional biopsy reporting a histopathological result of lichenoid mucositis consistent with oral lichen planus. Because of the increasing use of rituximab, it is necessary to know and recognize this uncommon side effect.

Microsimulation Modeling in Oncology

PURPOSE

Microsimulation is a modeling technique that uses a sample size of individual units (microunits), each with a unique set of attributes, and allows for the simulation of downstream events on the basis of predefined states and transition probabilities between those states over time. In this article, we describe the history of the role of microsimulation in medicine and its potential applications in oncology as useful tools for population risk stratification and treatment strategy design for precision medicine.

METHODS

We conducted a comprehensive and methodical search of the literature using electronic databases-Medline, Embase, and Cochrane-for works published between 1985 and 2016. A medical subject heading search strategy was constructed for Medline searches by using a combination of relevant search terms, such as "microsimulation model medicine," "multistate modeling cancer," and "oncology."

RESULTS

Microsimulation modeling is particularly useful for the study of optimal intervention strategies when randomized control trials may not be feasible, ethical, or practical. Microsimulation models can retain memory of prior behaviors and states. As such, it allows an explicit representation and understanding of how various processes propagate over time and affect the final outcomes for an individual or in a population.

CONCLUSION

A well-calibrated microsimulation model can be used to predict the outcome of the event of interest for a new individual or subpopulations, assess the effectiveness and cost effectiveness of alternative interventions, and project the future disease burden of oncologic diseases. In the growing field of oncology research, a microsimulation model can serve as a valuable tool among the various facets of methodology available.