A Generic Model for Follicular Lymphoma: Predicting Cost, Life Expectancy, and Quality-Adjusted-Life-Year Using UK Population-Based Observational Data

Patient-level simulation models in cancer care: a systematic review

Background

Patient-level simulation (PLS) models overcome some major limitations of conventional cohort models and have broad applicability in healthcare, yet limited knowledge exists about their potential in cancer care.

Objectives

This systematic review aims to: (1) describe the application areas of PLS models in cancer care, (2) identify commonly used model structures, (3) evaluate the quality of reporting based on established guidelines, and (4) critically discuss the potential and limitations of PLS models in this context.

Methods

A systematic literature search was completed in Web of Science, PubMed, EMBASE and EconLit. Reasons underlying the use of PLS models were identified with a conventional inductive content analysis and reporting quality was assessed with an 18-item checklist based on the ISPOR-SMDM guidelines.

Results

The number of publications increased over time and most studies used state-transition microsimulation (49.25%) or discrete event simulation (48.51%). Two main application areas could be discerned, namely disease progression modelling (DPM) (78.36%) and health and care systems operation (HCSO) (21.64%). In the DPM domain, the use of PLS models was mainly motivated by the need to represent patient heterogeneity and history. In the HCSO domain, PLS models were used to better understand and improve cancer care delivery. Average reporting quality was 65.2% and did not improve over time.

Conclusion

PLS models can be used to simulate the progression of cancer and to model cancer care delivery. In the DPM domain more direct comparisons with cohort models are required to establish the relative advantages of PLS models and in the HCSO domain the impact on clinical practice needs to be systematically assessed. Furthermore, adherence to the ISPOR-SMDM guidelines should be improved.

Burden of Illness in Follicular Lymphoma with Multiple Lines of Treatment, Italian RWE Analysis

This real-world analysis investigated patients with follicular lymphoma in Italy receiving three or more treatment lines (≥3L), focusing on therapeutic pathways with their rebounds on healthcare resource consumptions and costs. Data were retrieved from administrative databases from healthcare entities covering about 13.3 million residents. Adults diagnosed with follicular lymphoma were identified between January 2015 and June 2020, and among them 2434 patients with ≥3L of treatment during the data availability interval (January 2009 to June 2021) were included. Of them, 1318 were in 3L, 494 in 4L and 622 in ≥5L. A relevant proportion of patients (12-32%) switched to a later line within the same calendar year. At 3-year follow-up (median), 34% patients died. Total mean annual expenses were euro 14,508 in the year preceding inclusion and rose to euro 21,081 at 1-year follow-up (on average euro 22,230/patient/year for the whole follow-up), with hospitalization and drug expenses as weightiest cost items. In conclusion, the clinical and economic burden of follicular lymphoma increases along with later treatment lines. The high mortality rates indicate that further efforts are needed to optimize disease management.

A scoping review on patient heterogeneity in economic evaluations of precision medicine based on basket trials

INTRODUCTION

Considerable challenges in the economic evaluation of precision medicines have been mentioned in previous studies. However, they have not addressed how an economic assessment would be conducted based on basket trials (novel studies for evaluation of precision medicine effects) in which the included populations have specific biomarkers and various cancers. Since basket trial populations have remarkable heterogeneity, this study aims to investigate the concept of heterogeneity and specific method(s) for considering it in economic evaluations through guidelines and studies that could be applicable in economic evaluation based on basket trials.

AREA COVERED

We searched PubMed, Web of Science, Scopus, Google Scholar, and Google to find studies and pharmacoeconomics guidelines. The inclusion criteria included subjects of patient heterogeneity and suggested explicit method(s). Thirty-nine guidelines and 43 studies were included and evaluated. None of these materials mentioned disease types in a target population as a factor causing heterogeneity. Moreover, in economic evaluations, patient heterogeneity has been considered with four general approaches subgroup analysis, individual-based models, sensitivity analysis, and regression models.

EXPERT OPINION

Type of disease is not considered a contributing factor in population heterogeneity, and the probable appropriate method for this issue could be individual-based models.

Discrete-Event Simulation Modeling in Healthcare: A Comprehensive Review

Discrete-event simulation (DES) is a stochastic modeling approach widely used to address dynamic and complex systems, such as healthcare. In this review, academic databases were systematically searched to identify 231 papers focused on DES modeling in healthcare. These studies were sorted by year, approach, healthcare setting, outcome, provenance, and software use. Among the surveys, conceptual/theoretical studies, reviews, and case studies, it was found that almost two-thirds of the theoretical articles discuss models that include DES along with other analytical techniques, such as optimization and lean/six sigma, and one-third of the applications were carried out in more than one healthcare setting, with emergency departments being the most popular. Moreover, half of the applications seek to improve time- and efficiency-related metrics, and one-third of all papers use hybrid models. Finally, the most popular DES software is Arena and Simul8. Overall, there is an increasing trend towards using DES in healthcare to address issues at an operational level, yet less than 10% of DES applications present actual implementations following the modeling stage. Thus, future research should focus on the implementation of the models to assess their impact on healthcare processes, patients, and, possibly, their clinical value. Other areas are DES studies that emphasize their methodological formulation, as well as the development of frameworks for hybrid models.

Lifetime Costs for Treated Follicular Lymphoma Patients in the US

BACKGROUND AND OBJECTIVE

The objective of this study was to estimate the lifetime costs of patients receiving treatment for follicular lymphoma (FL) in the United States.

METHODS

A Markov model was programmed in hēRo3 with a 6-month cycle length, 35-year time horizon (lifetime projection), and health states for line of treatment, response, receipt of maintenance therapy among responders, transformation to diffuse large B-cell lymphoma (DLBCL), development of second primary malignancy (SPM), and death. The model was used to estimate the expected lifetime costs of FL (in 2019 USD), including costs of drug acquisition and administration, transplant procedures, radiotherapy, adverse events, follow-up, DLBCL, SPM, end-of-life care, and indirect costs. Model inputs were based on published sources.

RESULTS

In the US, patients with FL receiving treatment have a life expectancy of approximately 14.5 years from initiation of treatment and expected lifetime direct and indirect costs of US$515,884. Costs of drugs for induction therapy represent the largest expenditure (US$233,174), followed by maintenance therapy costs (US$88,971) and terminal care costs (US$57,065). Despite the relatively advanced age of these patients, indirect costs (due to patient morbidity and mortality and caregiver lost work time) represent a substantial share of total costs (US$40,280). Treated FL patients spend approximately 6.9 years in the health states associated with first-line therapy. Approximately 66 and 46% continue to second- and third-line therapies, respectively. The mean (95% credible interval) of expected lifetime costs based on the probabilistic sensitivity analyses was US$559,202 (421,997-762,553).

CONCLUSIONS

In the US, the expected lifetime costs of care for FL patients who receive treatment is high. The results highlight the potential economic benefits that might be achieved by treatments for FL that prevent or delay disease progression.

Epidemiology of diffuse large B-cell lymphoma (DLBCL) and follicular lymphoma (FL) in the United States and Western Europe: population-level projections for 2020-2025

Diffuse large B-cell lymphoma (DLBCL) and follicular lymphoma (FL) treatments have been rapidly evolving for patients treated in later lines of therapy (LoT). Country-specific cancer registry data for the US and Western Europe (WE) were combined with physician survey results to project the incidence, prevalence, and number of DLBCL and FL patients eligible for and treated by LoT between 2020 and 2025. The total number of incidents and prevalent cases of DLBCL and FL is expected to increase between 2020 and 2025 in the US and WE. 56% and 53% of the third line plus (3L+) eligible DLBCL patients and 60% and 55% of eligible FL patients initiated treatment in the US and WE, respectively. Further research is warranted to understand the reasons behind the high proportion of treatment eligible patients who do not initiate treatment, and potential differences between countries, especially in the 3L + settings.

Onwards and Upwards: A Systematic Survey of Economic Evaluation Methods in Oncology

INTRODUCTION

The type of methods used in economic evaluations of health technology can lead to results that may influence decisions. Despite the potential impact on decision making, there is very little documentation of methods used in economic evaluation in oncology pertaining to key assumptions and extrapolation methods of survival benefits, especially in terms of survival analysis techniques and methods for extrapolation.

OBJECTIVES

The primary objectives of this study were to identify, examine, and describe the methods used in economic evaluations in oncology over a 10-year period, while secondary objectives included examining the use of identified methods across different geographic regions.

METHODS

A systematic search of the published oncology literature was conducted to identify economic evaluations of advanced or metastatic cancers published between 2010 and 2019 using the PUBMED, Ovid MEDLINE, and EMBASE databases. A random sample was taken, and information on type of study, data source, modeling techniques, and survival analysis methods were abstracted and descriptively summarized.

RESULTS

A total of 8481 abstracts were identified and 76 economic evaluations were abstracted and assessed. Most identified studies were from North America (38%), East Asia (21%), continental Europe (18%), or the UK (16%), and most commonly focused on lung cancer (18%), colorectal cancer (16%), or breast cancer (13%). A large majority of studies were based on data from randomized controlled trials (82%), utilized a cost-utility approach (82%), and took a public healthcare system perspective (83%). Common model structures included Markov (49%) and partitioned survival (17%). Fitted parametric curves were the most commonly used extrapolation method (89%) for overall survival and most often utilized the Weibull distribution (64%). Secondary assessments showed modest regional variation in the use of identified methods, including the use of fitted parametric curves, testing of the proportional hazards assumption, and validation of results.

CONCLUSION

A majority of papers in the study sample reported basic characteristics of study type, data source used, modeling techniques, and utilization of survival analysis methods. However, greater detail in reporting extrapolation methods, statistical analyses, and validation of results could be potential improvements, especially across regions, in order to support greater consistency in decision making. Future research could document the diffusion of novel modeling techniques into economic evaluation.

Positron-emission tomography-based staging is cost-effective in early-stage follicular lymphoma

The objective was to assess the cost-effectiveness of staging PET/CT in early-stage follicular lymphoma (FL) from the Canadian health-care system perspective. Methods: The study population was FL patients staged as early-stage using conventional CT imaging and planned for curative-intent radiation therapy (RT). A decision analytic model simulated the management after adding staging PET/CT versus using staging CT alone. In the no-PET/CT strategy, all patients proceeded to curative-intent RT as planned. In the PET/CT strategy, PET/CT information could result in an increased RT volume, switching to a noncurative approach, or no change in RT treatment as planned. The subsequent disease course was described using a state-transition cohort model over a 30-y time horizon. Diagnostic characteristics, probabilities, utilities, and costs were derived from the literature. Baseline analysis was performed using quality-adjusted life years (QALYs), costs (2019 Canadian dollars), and the incremental cost-effectiveness ratio. Deterministic sensitivity analyses were conducted, evaluating net monetary benefit at a willingness-to-pay threshold of $100,000/QALY. Probabilistic sensitivity analysis using 10,000 simulations was performed. Costs and QALYs were discounted at a rate of 1.5%. Results: In the reference case scenario, staging PET/CT was the dominant strategy, resulting in an average lifetime cost saving of $3,165 and a gain of 0.32 QALYs. In deterministic sensitivity analyses, the PET/CT strategy remained the preferred strategy for all scenarios supported by available data. In probabilistic sensitivity analysis, the PET/CT strategy was strongly dominant in 77% of simulations (i.e., reduced cost and increased QALYs) and was cost-effective in 89% of simulations (i.e., either saved costs or had an incremental cost-effectiveness ratio below $100,000/QALY). Conclusion: Our analysis showed that the use of PET/CT to stage early-stage FL patients reduces cost and improves QALYs. Patients with early-stage FL should undergo PET/CT before curative-intent RT.

Comparative effectiveness study of chemotherapy in follicular lymphoma patients in the rituximab era: a Japanese claims database study

Aim: To evaluate comparative effectiveness of rituximub (R)-based versus non-R-based therapies for follicular lymphoma patients in Japan, where limited studies have been reported. Materials & methods: Patients who received R-based index regimens were propensity score matched to those who did not receive R, based on patient baseline attributes and clinical characteristics using Japanese retrospective claims database to assess clinical and economic outcomes. Results & conclusion: A total of 1947 patients remained in the overall follicular lymphoma cohorts: 1294 receiving an R-based and 653 a non-R-based regimen. Patients on R-based therapy underwent fewer hospitalizations and had a shorter length of stay, but had higher costs during the first year of intensive R-based therapy. Improved clinical outcomes were associated with patients who were younger, female and chose R-based regimens in first index line.

Treatment Patterns and Health Care Costs in Commercially Insured Patients with Follicular Lymphoma

BACKGROUND

Few studies have estimated the real-world economic burden such as all-cause and follicular lymphoma (FL)-related costs and health care resource utilization (HCRU) in patients with FL.

OBJECTIVES

This study evaluated outcomes in patients who were newly initiated with FL indicated regimens by line of therapy with real-world data.

METHODS

A retrospective study was conducted among patients with FL from MarketScan^® databases between January 1, 2010 and December 31, 2013. Patients were selected if they were ≥18 years old when initiated on a FL indicated therapy, had at least 1 FL-related diagnosis, ≥1 FL commonly prescribed systemic anti-cancer therapy after diagnosis, and did not use any FL indicated regimen in the 24 months prior to the first agent. These patients were followed up at least 48 months and the outcomes, including the distribution of regimens by line of therapy, the treatment duration by line of therapy, all-cause and FL-related costs, and HCRU by line of therapy were evaluated.

RESULTS

This study identified 598 patients who initiated FL indicated treatment. The average follow-up time was approximately 5.7 years. Of these patients, 50.2% (n=300) were female, with a mean age of 60.7 years (SD=13.1 years) when initiating their treatment with FL indicated regimens. Overall, 598 (100%) patients received first-line therapy, 180 (43.6%) received second-line therapy, 51 received third-line therapy, 21 received fourth-line therapy, and 10 received fifth-line therapy. Duration of treatment by each line of therapy was 370 days, 392 days, 162 days, 148 days, and 88 days, respectively. The most common first-line regimens received by patients were rituximab (n=201, 33.6%), R-CHOP (combination of rituximab, cyclophosphamide, doxorubicin hydrochloride [hydroxydaunomycin]; n=143, 24.0%), BR (combination of bendamustine and rituximab; n=143, 24.0%), and R-CVP (combination of rituximab, cyclophosphamide, vincristine, and prednisone; n=71, 11.9%). The most common second-line treatment regimens were (N=180): rituximab (n=78, 43.3%) and BR (n=41, 22.8%). Annualized all-cause health care costs per patient ranged from US$97 141 (SD: US$144 730) for first-line to US$424 758 (SD: US$715 028) for fifth-line therapy.

CONCLUSIONS

The primary regimens used across treatment lines conform to those recommended by the National Comprehensive Cancer Network clinical practice guidelines. The economic burden for patients with FL is high and grows with subsequent lines of therapy.

How to Address Uncertainty in Health Economic Discrete-Event Simulation Models: An Illustration for Chronic Obstructive Pulmonary Disease

Background. Evaluation of personalized treatment options requires health economic models that include multiple patient characteristics. Patient-level discrete-event simulation (DES) models are deemed appropriate because of their ability to simulate a variety of characteristics and treatment pathways. However, DES models are scarce in the literature, and details about their methods are often missing. Methods. We describe 4 challenges associated with modeling heterogeneity and structural, stochastic, and parameter uncertainty that can be encountered during the development of DES models. We explain why these are important and how to correctly implement them. To illustrate the impact of the modeling choices discussed, we use (results of) a model for chronic obstructive pulmonary disease (COPD) as a case study. Results. The results from the case study showed that, under a correct implementation of the uncertainty in the model, a hypothetical intervention can be deemed as cost-effective. The consequences of incorrect modeling uncertainty included an increase in the incremental cost-effectiveness ratio ranging from 50% to almost a factor of 14, an extended life expectancy of approximately 1.4 years, and an enormously increased uncertainty around the model outcomes. Thus, modeling uncertainty incorrectly can have substantial implications for decision making. Conclusions. This article provides guidance on the implementation of uncertainty in DES models and improves the transparency of reporting uncertainty methods. The COPD case study illustrates the issues described in the article and helps understanding them better. The model R code shows how the uncertainty was implemented. For readers not familiar with R, the model's pseudo-code can be used to understand how the model works. By doing this, we can help other developers, who are likely to face similar challenges to those described here.

Exploring the Impact of Quality of Life on Survival: A Case Study in Total Knee Replacement Surgery

Background. There is growing evidence that quality of life (QoL) has a strong association with mortality. However, incorporation of QoL is uncommon in standard survival modeling. Methods. Using data extracted from a registry of patients undergoing total knee replacement (TKR), the impact of incorporating QoL in survival modeling was explored using 4 parametric survival models. QoL was incorporated and tested in 2 forms, which are baseline and change in QoL due to intervention. Life expectancy and quality-adjusted life years (QALYs) were calculated and comparisons made to a reference model (no QoL) to translate the findings in the context of modeled economic evaluations. Results. A total of 2858 TKR cases (2309 patients) who had TKR between 2006 and 2015 were included in this analysis. Increases in baseline and change in QoL were associated with a reduction in mortality. Compared to the reference model, differences of up to 0.32 life years and 0.53 QALYs were observed, and these translated into a 9.5% change in incremental effectiveness. These differences were much larger as the strength of the association between QoL and mortality increased. Conclusions. This work has demonstrated that the inclusion of QoL measures (at baseline and change from baseline) when extrapolating survival does matter. It can influence health outcomes such as life expectancy and QALYs, which are relevant in cost-effectiveness analysis. This is important because neglecting the correlation between QoL and mortality can lead to imprecise extrapolations and thus risk misleading results affecting subsequent decisions made by policy makers.

Real-world costs of illness of Hodgkin and the main B-Cell Non-Hodgkin lymphomas in France

Background: Lymphomas are costly diseases that suffer from a lack of detailed economic information, notably in a real-world setting. Decision-makers are increasing the search for Real-World Evidence (RWE) to assess the impact, in real-life, of healthcare management and to support their public decisions. Thus, we aimed to assess the real-world net costs of the active treatment phases of adult Hodgkin Lymphoma (HL), Follicular Lymphoma (FL) and Diffuse Large B Cell Lymphoma (DLBCL).Methods: We performed a retrospective cohort study using population-based data from a national representative sample of the French population covered by the health insurance system. Cost analysis was performed from the French health insurance perspective and took into account direct and sick leave compensation costs (€2,018). Healthcare costs were studied over the active treatment phase. We used multivariate modeling to adjust cost differences between lymphoma subtypes.Results: Analyses were performed on 224 lymphoma patients and 896 controls. The mean additional monthly costs due to HL, FL and DLBCL patients were respectively €5,188, €3,242 and €7,659 for the active treatment phase. The main additional cost driver was principally inpatient stay (hospitalization costs and costly cancer-related drugs), followed by outpatient medication and productivity loss. When adjusted, DLBCL remains significantly the most costly lymphoma subtype.Conclusion: This study provides an accurate assessment of the main lymphoma subtypes related cost with high magnitude of details in a real-world setting. We underline where potential cost saving could be realized via the use of biosimilar medication, and where lymphoma management could be improved with the early management of adverse events.KEY POINTSThis is one of the first studies which assess the additional cost of lymphoma in Europe, according the main sub-types of lymphoma and with real-world database.The additional monthly cost due to HL, FL and DLBCL patients were respectively €5,188, €3,242 and €7,659 for the active treatment phase and the main additional cost driver was principally inpatient stay (i.e. hospitalization costs and additional inpatient medicines, notably rituximab), followed by outpatient medication and productivity loss.This study provides an accurate and detailed lymphoma subtype cost description and comparison which supply data for efficiency evaluations and will allow French health policy to improve lymphoma management.

Health Technology Assessment Challenges in Oncology: 20 Years of Value in Health

BACKGROUND

Oncology treatments have changed from chemotherapies to targeted therapies and more recently immuno-oncology. This has posed special challenges in the field of health technology assessment (HTA): capturing quality of life (QOL) associated with toxicity due to chemotherapy, crossover upon progression in targeted therapy trials, and survival extrapolation for immuno-oncology drugs.

OBJECTIVES

To showcase 20 years of Value in Health (ViH) publications in oncology.

METHODS

A review was undertaken of oncology articles published in ViH from May 1998 to August 2018. Full-length articles published in ViH with the keywords "oncology," "cancer," "h(a)ematology," and "malignancy" were included for review. Conference abstracts were excluded.

RESULTS

Four major themes were identified: (1) QOL and the development of multiple functional assessment of cancer therapy tools and mapping instruments; (2) analysis of clinical evidence using indirect comparisons, network analyses, and adjustment for crossovers; (3) modeling, Markov models, partitioned survival models, and extrapolation methods; and (4) financial implications and how to deal with uncertainty, introduction of conditional reimbursement, managed entry, and risk share agreements.

DISCUSSION

This review article highlights the important role ViH has played in disseminating HTA research in oncology. A few key issues loom on the horizon: precision medicine, further development and practical application of new QOL measures, methods for translating clinical evidence, and exploration of modeling techniques. For a better understanding of the complex interplay between access and financial risk management, ViH will no doubt continue to promote pioneering research in HTA and oncology.