Recent discoveries in molecular diagnostics and drug treatments have improved the treatment of patients with advanced (inoperable) non-squamous non-small cell lung cancer (NSCLC) from solely ...platinum-based chemotherapy to more personalized treatment, including targeted therapies and immunotherapies. However, these improvements come at considerable costs, highlighting the need to assess their cost-effectiveness in order to optimize lung cancer care. Traditionally, cost-effectiveness models for the evaluation of new lung cancer treatments were based on the findings of the randomized control trials (RCTs). However, the strict RCT inclusion criteria make RCT patients not representative of patients in the real-world. Patients in RCTs have a better prognosis than patients in a real-world setting. Therefore, in this study, we developed and validated a diagnosis-treatment decision model for patients with advanced (inoperable) non-squamous NSCLC based on real-world data in the Netherlands. The model is a patient-level microsimulation model implemented as discrete event simulation with five health events. Patients are simulated from diagnosis to death, including at most three treatment lines. The base-model (non-personalized strategy) was populated using real-world data of patients treated with platinum-based chemotherapy between 2008 and 2014 in one of six Dutch teaching hospitals. To simulate personalized care, molecular tumor characteristics were incorporated in the model based on the literature. The impact of novel targeted treatments and immunotherapies was included based on published RCTs. To validate the model, we compared survival under a personalized treatment strategy with observed real-world survival. This model can be used for health-care evaluation of personalized treatment for patients with advanced (inoperable) NSCLC in the Netherlands.
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IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
Objective
Clinical outcome data on patients with extensive disease small cell lung cancer (ED SCLC) treated in routine practice is limited. The aim of this retrospective study is to present data on ...treatment patterns and survival in an unselected patient population with ED SCLC.
Methods
All patients diagnosed with ED SCLC between 2008 and 2014 in six Dutch large teaching hospitals (Santeon network) were included. We collected data on patient characteristics, systemic treatments, overall survival (OS), dose reductions (<80% of initial dose) and early discontinuation (<4 cycles).
Results
From 792 diagnosed patients, 568 (72%) started with first‐line treatment. Of these patients, 41% received second‐line treatment. Only 68 patients received third‐line treatment. For all treated patients, the mean age was 66 years. The majority (72%) had a performance status (ECOG) of 0 or 1 at diagnosis. Median OS of treated patients was 7.4 months. Of all patients with first‐line treatment, 26% received <4 cycles and dose reductions were observed in 29%.
Conclusion
After first‐line systemic treatment in ED SCLC the fraction of patients receiving subsequent lines of treatment is rapidly decreasing. This information is necessary as background for evaluation of the added value of future drugs under study for ED SCLC.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
Purpose
The aim of this study is to assess how clinical outcomes in real‐world (effectiveness) correspond to the outcomes in clinical trials (efficacy) of systemic treatments for extensive disease ...small cell lung cancer (ED SCLC).
Methods
All patients diagnosed with ED SCLC between 2008 and 2014 in six Dutch large teaching hospitals (Santeon network) were identified and followed‐up from date of diagnosis until death or end of data collection. For every patient, an efficacy‐effectiveness factor (EE factor) was calculated by dividing individual patients' overall survival (OS) by the pooled median OS assessed from clinical trials with the respective treatment.
Results
From 792 diagnosed patients, 568 (72%) started with first‐line treatment. Overall, the median EE factor was 0.79 (P < .001 from 1.00). Poor performance status (ECOG≥2) and a higher age at diagnosis (age ≥ 65 years) were independent predictors for a lower EE factor. The EE gap was 43% in patients with both age ≥ 65 years and ECOG ≥2 (EE factor 0.57). The mean age and the proportion of patients with ECOG≥2 in real‐world were different from those in clinical trials (mean age of 66 versus 62 years, and ECOG≥2 25% versus 17%; both P < .001).
Conclusion
OS of patients with ED SCLC treated with systemic therapy in real‐world practice is 21% shorter than for patients included in trials. Age at diagnosis and performance status partly explain this gap.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
This study aims to assess how clinical outcomes of immunotherapy in real-world (effectiveness) correspond to outcomes in clinical trials (efficacy) and to look into factors that might explain an ...efficacy-effectiveness (EE) gap. All patients diagnosed with stage IV non-small cell lung cancer (NSCLC) in 2015-2018 in six Dutch large teaching hospitals (Santeon network) were identified and followed-up from date of diagnosis until death or end of data collection. Progression-free survival (PFS) and overall survival (OS) from first-line (1L) pembrolizumab and second-line (2L) nivolumab were compared with clinical trial data by calculating hazard ratios (HRs). From 1950 diagnosed patients, 1005 (52%) started with any 1L treatment, of which 83 received pembrolizumab. Nivolumab was started as 2L treatment in 141 patients. For both settings, PFS times were comparable between real-world and trials (HR 1.08 (95% CI 0.75-1.55), and HR 0.91 (95% CI 0.74-1.14), respectively). OS was significantly shorter in real-world for 1L pembrolizumab (HR 1.55; 95% CI 1.07-2.25). Receiving subsequent lines of treatment was less frequent in real-world compared to trials. There is no EE gap for PFS from immunotherapy in patients with stage IV NSCLC. However, there is a gap in OS for 1L pembrolizumab. Fewer patients proceeding to a subsequent line of treatment in real-world could partly explain this.
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IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
The divergence between clinical trial results and real-world outcomes is largely unknown for many cancer types. The present study aims overall to assess the efficacy-effectiveness gap (difference ...between outcomes in clinical trials and the real world) in systemic treatment for metastatic nonsmall cell lung cancer (NSCLC).All patients diagnosed with stage IV NSCLC between 2008 and 2014 within a network of seven Dutch large teaching hospitals (Santeon) were studied. For every patient, an efficacy-effectiveness (EE) factor was calculated by dividing individual patients' overall survival (OS) by the pooled median OS assessed from clinical trials with the respective treatment.From 2989 diagnosed patients, 1214 (41%) started with first-line treatment. For all studied regimens, real-world OS was shorter than OS reported in clinical trials. Overall, the EE factor was 0.77 (95% CI 0.70-0.85; p<0.001). Real-world patients completed their treatment plan less often and proceeded less frequently to further lines of treatment. These parameters together with Eastern Cooperative Oncology Group performance status explained 35% of the variation in EE factor.Survival of patients with metastatic NSCLC treated with chemotherapy or targeted therapy in real-world practice is nearly one-quarter shorter than for patients included in trials. Patients' performance status, earlier discontinuation and fewer subsequent lines of treatment partly explained this difference.
ObjectivesMeasuring quality of care is important, however many of the quality indicators used do not focus on outcome of treatment and aspects which are valuable for patients and physicians. The ...project ‘Care for Outcomes’ aims to establish a relevant set of outcome indicators for lung cancer.SettingNetwork of seven large, non-university teaching hospitals in the Netherlands (Santeon).MethodsBy reviewing the literature, a list of potential outcome indicators for patients with lung cancer was composed and subsequently prioritised by expert’s opinion. Three external parties, with expertise on lung cancer, clinical management and public health, evaluated and reduced the list of indicators to a working set. Finally, the resulting selection of outcome indicators was tested for feasibility and discrimination in patient data, by collecting retrospective data and performing regression and survival analyses.ParticipantsDevelopment of the indicator set in six Santeon hospitals. Retrospective cohort study in 5922 patients diagnosed with lung cancer (all types and stages).ResultsSelected outcome indicators were divided into three levels of outcome (tiers). The first tier about survival and the process of recovery include mortality, survival, positive resection margins, rethoracotomy after resection and quality of life at baseline and after 3, 6 and 12 months. Tier 2 concerning the sustainability of the recovery include complications after resection and toxicity after chemotherapy and/or radiation. Tier 3 about sustainability of health revealed no measurable outcomes. The retrospective data collection showed differences between hospitals and variation in case mix.ConclusionA relevant set of outcome indicators for lung cancer was systematically developed. This set has the potential to compare quality of care between hospitals and inform patients with lung cancer about outcomes. The project is ongoing in the current Santeon Value-Based Health Care programme through quality and improvement cycles.
Introduction
Patients treated with immunotherapy are divided into two subgroups: (i) long-term survivors (LTS) and (ii) moderate survivors. Nevertheless, clinical trials (RCTs) report only average ...treatment effects such as hazard rate (HRs). Health economic-models often only input average treatment effects, even though it has been shown that accounting for the LTS subgroup is crucial for accurate projection of long-term survival under immunotherapy. We investigated the incorporation of a statistical mixture cure model (MCM) in a health-economic model for lung cancer as a way to account for LTS while incorporating reported average RCT-based treatment effects.
Methods
We developed a microsimulation model describing disease progression under three treatment lines in advanced lung cancer using Dutch real-world data of chemotherapies treated patients. Here we focus on first-line treatment, for which we used gompertz distribution to simulate time-to-progression. To simulate the impact of immunotherapy, we adjusted base-model assuming MCM for first-line treatment, where the LTS subgroup was not at risk to progress, but instead die from background mortality. The subgroup of moderate survivors on the other hand are at risk to progress with adjusted progression-free HR (PF-HR). We simulated the model with size of LTS (prop_LTS) ranging from 14-34 percent (keynote-001 five-year overall survival OS, 95% confidence interval) while fixing average RCT PF-HR at 0.5. Model predictions under the different prop_LTS were compared to real-world Dutch OS as well as the long-term RCT five-year OS.
Results
With respect to observed short-term survival outcomes, model predictions were insensitive to assumptions regarding the size of the LTS subgroup. However, to match the five-year RCT OS rate reported (32%), the prop_LTS had to be equal to 34 percent. Under this latter setting for the prop_LTS, the progression HR in the subgroup of moderate survivors was calibrated to be 1.1.
Conclusions
The use of a mixture cure model improves long-term model-based projections with the implicit assumption that moderate survivors have little or no treatment benefit.
Background
The Value-Based Health Care concept defines patient value as patient-relevant outcomes divided by costs. The aim of the present study was to assess the development of systemic treatment ...costs over the years compared with changes in overall survival (OS) at the level of a diagnosis of stage IV non-small cell lung cancer (NSCLC).
Methods
All patients diagnosed (in 2008–2014) with stage IV NSCLC and treated with systemic treatment in six Dutch large teaching hospitals (Santeon network) were included. We collected data on OS and amounts of drug units (milligrams) for every drug in the applied systemic cancer treatments, until death. These amounts were multiplied by Dutch unit costs (Euros/mg) expressed in 2018 Euros to construct total drug costs per line of treatment per patient. Costs for day care visits were added for drugs requiring parenteral administration.
Results
Data were collected from 1214 patients. Median OS and mean total drug costs showed no significant variation over the years (
p
= 0.437 and
p
= 0.693, respectively). Mean total drug costs per 1 year of survival ranged from €20,665 to €26,438 during the period under study. Costs for first-line systemic treatment were significantly higher in 2011–2014 compared with 2008–2010.
Conclusion
This study shows that overall drug costs were stable over the years, despite a relative increase in first-line treatment costs. Median OS remained at around 8 months from year to year. These trend data are very relevant as background for the assessment of costs and achieved outcomes in the more recent years.
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