Exploratory Cost-Effectiveness Analysis of Response-Guided Neoadjuvant Chemotherapy for Hormone Positive Breast Cancer Patients

How is overall survival assessed in randomised clinical trials in cancer and are subsequent treatment lines considered? A systematic review

BACKGROUND

Overall survival is the "gold standard" endpoint in cancer clinical trials. It plays a key role in determining the clinical- and cost-effectiveness of a new intervention and whether it is recommended for use in standard of care. The assessment of overall survival usually requires trial participants to be followed up for a long period of time. In this time, they may stop receiving the trial intervention and receive subsequent anti-cancer treatments, which also aim to extend survival, during trial follow-up. This can potentially change the interpretation of overall survival in the context of the clinical trial. This review aimed to determine how overall survival has been assessed in cancer clinical trials and whether subsequent anti-cancer treatments are considered.

METHODS

Two searches were conducted using MEDLINE within OVID© on the 9th of November 2021. The first sought to identify papers publishing overall survival results from randomised controlled trials in eight reputable journals and the second to identify papers mentioning or considering subsequent treatments. Papers published since 2010 were included if presenting or discussing overall survival in the context of treating cancer.

RESULTS

One hundred and thirty-four papers were included. The majority of these were presenting clinical trial results (98, 73%). Of these, 45 (46%) reported overall survival as a (co-) primary endpoint. A lower proportion of papers including overall survival as a (co-) primary endpoint compared to a secondary endpoint were published in recent years. The primary analysis of overall survival varied across the papers. Fifty-nine (60%) mentioned subsequent treatments. Seven papers performed additional analysis, primarily when patients in the control arm received the experimental treatment during trial follow-up (treatment switching).

DISCUSSION

Overall survival has steadily moved from being the primary to a secondary endpoint. However, it is still of interest with papers presenting overall survival results with the caveat of subsequent treatments, but little or no investigation into their effect. This review shows that there is a methodological gap for what researchers should do when trial participants receive anti-cancer treatment during trial follow-up. Future research will identify the stakeholder opinions, on how this methodological gap should be addressed.

Health-related quality of life and productivity costs in breast cancer patients treated with tamoxifen in the Netherlands

The aim of this study was to describe health-related quality of life (HRQoL) and productivity in Dutch breast cancer patients treated with tamoxifen in an adjuvant setting. Patients who started treatment with a standard dose of tamoxifen and who gave written informed consent, were eligible for participation in this trial. A total of 145 patients were asked to complete a survey at 3 months (T1) and 6 months (T2) after initiation of tamoxifen. HRQoL was measured by the EQ-5D-5L and the FACT-B questionnaire, and productivity by using the iMTA Productivity Costs Questionnaire. At 3 months 137 (95%) and at 6 months 133 (92%) patients responded to the surveys. EQ-5D-5 L utility values for T1 and T2 were 0.81 ± 0.17 and 0.81 ± 0.18, respectively. FACT-B scores for T1 and T2 were 109 ± 17.9 and 108 ± 20.0, respectively. No differences in both EQ-5D-5 L utility and FACT-B scores were found between T1 and T2 (p > 0.05). Age and employment status were statistically significantly associated with FACT-B scores (p = 0.04 and p = 0.03, respectively), indicating that younger and unemployed respondents had lower FACT-B scores. Importantly, both short-term and long-term productivity improved during the first six months of tamoxifen treatment (p < 0.05). Here, short-term productivity losses (consisting of absenteeism, presenteeism and unpaid work) for T1 and T2 were estimated at € 855,- and € 396,-, respectively. Long-term productivity losses (consisting of absenteeism) for T1 and T2 were estimated at € 2876,- and € 1104,-, respectively. In conclusion, this study presents HRQoL scores using different instruments and detailed loss of productivity estimates for breast cancer patients treated with adjuvant endocrine therapy. The results presented here can be used to inform input parameters in health economic evaluations of interventions for patients with breast cancer in the Netherlands and other Western countries and ultimately support decision making.

Cost-effectiveness of adding atezolizumab to first-line chemotherapy in patients with advanced triple-negative breast cancer

Background:

The effectiveness of atezolizumab plus nab-paclitaxel for advanced triple-negative breast cancer (TNBC) has been demonstrated. We aimed to evaluate its cost-effectiveness on advanced TNBC from the US payer perspective.

Methods:

A Markov model was adopted to project the disease course of newly diagnosed advanced TNBC. The clinical data were gathered from the IMpassion130 trial. Cost and health preference data were derived from the literature. The incremental cost-effectiveness ratio (ICER) was measured, and one-way sensitivity analysis and probabilistic sensitivity analysis were performed for exploring the model uncertainties.

Results:

Our results demonstrated that atezolizumab plus nab-paclitaxel augmented versus nab-paclitaxel therapy cost $104,278 and $149,465 and yielded an additional 0.371 and 0.762 of quality-adjusted life year (QALY) in in all patients with unknown PD-L1 status and subpopulation with PD-L1-positive, respectively, which led to an ICER of $281,448 and $196,073 per QALY gained. In all patients with unknown PD-L1 status, atezolizumab plus nab-paclitaxel treatment guiding by PD-L1 expression testing resulted in an ICER of $183,508 per QALY gained. Atezolizumab plus nab-paclitaxel could maintain a trend of positive incremental net health benefits and >50% probabilities of cost-effectiveness at the threshold of $200,000/QALY in more than half of subgroups with PD-L1-positive. One-way and probabilistic sensitivity analyses revealed the results were most sensitive to the hazard ratios (HRs) of overall survival (OS) of atezolizumab plus nab-paclitaxel versus nab-paclitaxel treatment.

Conclusion:

The atezolizumab plus nab-paclitaxel treatment is likely to be a cost-effective option compared with chemotherapy based on nab-paclitaxel for the patients with PD-L1-positive advanced TNBC.

Decision analytic modeling was useful to assess the impact of a prediction model on health outcomes before a randomized trial

OBJECTIVE

To demonstrate how decision analytic models (DAMs) can be used to quantify impact of using a (diagnostic or prognostic) prediction model in clinical practice and provide general guidance on how to perform such assessments.

STUDY DESIGN AND SETTING

A DAM was developed to assess the impact of using the HEART score for predicting major adverse cardiac events (MACE). Impact on patient health outcomes and health care costs was assessed in scenarios by varying compliance with and informed deviation (ID) (using additional clinical knowledge) from HEART score management recommendations. Probabilistic sensitivity analysis was used to assess estimated impact robustness.

RESULTS

Impact of using the HEART score on health outcomes and health care costs was influenced by an interplay of compliance with and ID from HEART score management recommendations. Compliance of 50% (with 0% ID) resulted in increased missed MACE and costs compared with usual care. Any compliance combined with at least 50% ID reduced both costs and missed MACE. Other scenarios yielded a reduction in missed MACE at higher costs.

CONCLUSION

Decision analytic modeling is a useful approach to assess impact of using a prediction model in practice on health outcomes and health care costs. This approach is recommended before conducting an impact trial to improve its design and conduct.

Cost-effectiveness of monitoring endoxifen levels in breast cancer patients adjuvantly treated with tamoxifen

PURPOSE

Breast cancer is the most common malignancy in women worldwide. Recurrence rates in breast cancer are considered to be dependent on the serum concentration of endoxifen, the active metabolite of tamoxifen. The goal of this study is to investigate the cost-effectiveness of periodically monitoring serum concentrations of endoxifen in adjuvant estrogen receptor alfa (ERα) positive breast cancer patients treated with tamoxifen in the Netherlands.

METHODS

A Markov model with disease-free survival (DFS), recurrent disease (RD), and death states was constructed. The benefit of drug monitoring was modeled via a difference in the fraction of patients achieving adequate serum concentrations. Robustness of results to changes in model assumptions were tested through deterministic and probabilistic sensitivity analyses.

RESULTS

Monitoring of endoxifen added 0.0115 quality-adjusted life-years (QALYs) and saved € 1564 per patient in the base case scenario. Deterministic sensitivity analysis demonstrated a large effect on the incremental cost-effectiveness ratio (ICER) of the differences in costs and utilities between the DFS and RD states. Probabilistic sensitivity analysis showed that the probability of cost-effectiveness at a willingness to pay of € 0 per quality-adjusted life-year (QALY) was 89.8%.

CONCLUSIONS

Based on this model, monitoring of endoxifen in adjuvant ERα + breast cancer patients treated with tamoxifen is likely to add QALYs and save costs from a healthcare payer perspective. We advise clinicians to consider integrating serum endoxifen concentration monitoring into standard adjuvant tamoxifen treatment of ERα + breast cancer patients.