Estimated Direct Costs of Renal Cancer by Stage of Disease at Diagnosis and Phase of Its Management: A Whole-Disease Model.

BACKGROUND: Renal cell carcinoma (RCC) is the seventh most common neoplasm in high-income countries. New clinical pathways have been developed to deal with this tumor, which includes costly drugs that pose an economic threat to the sustainability of healthcare services. This study provides an estimate of the direct costs of care for patients with RCC by stage of disease (early vs. advanced) at diagnosis, and disease management phase along the pathway recommended by local and international guidelines. MATERIALS AND METHODS: Considering the clinical pathway for RCC adopted in the Veneto region (north-east Italy) and the latest guidelines, we developed a very detailed "whole-disease" model that covers the probabilities of all potentially necessary diagnostic and therapeutic actions involved in the management of RCC. Based on the cost of each procedure according to the Veneto Regional Authority's official reimbursement tariffs, we estimated the total and average per-patient costs by stage of disease (early or advanced) and phase of its management. RESULTS: In the first year after diagnosis, the mean expected cost of a patient with RCC is €12,991 if it is localized or locally-advanced and reaches €40,586 if it is advanced. For early disease, the main cost is incurred by surgery, whereas medical therapy (first and second line) and supportive care become increasingly important for metastatic disease. CONCLUSION: It is crucially important to examine the direct costs of care for RCC, and to predict the burden on healthcare services of new oncological therapies and treatments, as the findings could be useful for policy-makers planning the allocation of resources.

Cost-effectiveness analysis of the new oncological drug durvalumab in Italian patients with stage III non-small cell lung cancer.

BACKGROUND: The monoclonal antibody durvalumab, an immune-checkpoint inhibitor (ICI) antiprogrammed death ligand 1 (PD-L1), is available for unresectable stage III NSCLC patients as consolidation therapy following induction chemoradiotherapy, with very promising overall survival (OS) and progression-free survial (PFS) results in registration trials. The purpose of this study was to provide policymakers with an estimate of the cost-effectiveness of durvalumab in the treatment of non-small cell lung cancer (NSCLC). METHODS: The study developed a Markov model covering a 5-year period to compare costs and outcomes of treating PD-L1 positive patients with or without durvalumab. We conducted a series of sensitivity analyses (Tornado analysis and Monte Carlo simulation) by varying some parameters to assess the robustness of our model and identify the parameters with the greatest impact on cost-effectiveness. RESULTS: Prior to the release of durvalumab, the management of NSCLC over a 5-year period cost €33 317 per patient, with an average life expectancy of 2.01 years. After the introduction of the drug, this increased to €37 317 per patient, with an average life expectancy of 2.13 years. Treatment with durvalumab led to an incremental cost-effectiveness ratio (ICER) of €35 526 per year. OS is the variable that contributes the most to the variability of the ICER. CONCLUSIONS: The study observed that durvalumab is a cost-effective treatment option for patients with unresectable stage III NSCLC.

Estimated direct costs of non-small cell lung cancer by stage at diagnosis and disease management phase: A whole-disease model.

BACKGROUND: Non-small cell lung cancer (NSCLC) is the first cause of cancer-related death among men and the second among women worldwide. It also poses an economic threat to the sustainability of healthcare services. This study estimated the direct costs of care for patients with NSCLC by stage at diagnosis, and management phase of pathway recommended in local and international guidelines. METHODS: Based on the most up-to-date guidelines, we developed a very detailed "whole-disease" model listing the probabilities of all potentially necessary diagnostic and therapeutic actions involved in the management of each stage of NSCLC. We assigned a cost to each procedure, and obtained an estimate of the total and average per-patient costs of each stage of the disease and phase of its management. RESULTS: The mean expected cost of a patient with NSCLC is 21,328 € (95% C.I. -20 897-22 322). This cost is 16 291 € in stage I, 19530 € in stage II, 21938 € in stage III, 22175 € in stage IV, and 28 711 € for a Pancoast tumor. In the early stages of the disease, the main cost is incurred by surgery, whereas in the more advanced stages radiotherapy, medical therapy, treatment for progressions, and supportive care become variously more important. CONCLUSIONS: An estimation of the direct costs of care for NSCLC is fundamental in order to predict the burden of new oncological therapies and treatments on healthcare services, and thus orient the decisions of policy-makers regarding the allocation of resources. KEY POINTS: SIGNIFICANT FINDINGS OF THE STUDY: The high costs of surgery make the early stages of the disease no less expensive than the advanced stages. WHAT THIS STUDY ADDS: An estimation of the direct costs of care is fundamental in order to orient the decisions of policy-makers regarding the allocation of resources.

Demographic and socio-economic factors, and healthcare resource indicators associated with the rapid spread of COVID-19 in Northern Italy: An ecological study.

BACKGROUND: COVID-19 rapidly escalated into a pandemic, threatening 213 countries, areas, and territories the world over. We aimed to identify potential province-level socioeconomic determinants of the virus's dissemination, and explain between-province differences in the speed of its spread, based on data from 36 provinces of Northern Italy. METHODS: This is an ecological study. We included all confirmed cases of SARS-CoV-2 reported between February 24th and March 30th, 2020. For each province, we calculated the trend of contagion as the relative increase in the number of individuals infected between two time endpoints, assuming an exponential growth. Pearson's test was used to correlate the trend of contagion with a set of healthcare-associated, economic, and demographic parameters by province. The virus's spread was input as a dependent variable in a stepwise OLS regression model to test the association between rate of spread and province-level indicators. RESULTS: Multivariate analysis showed that the spread of COVID-19 was correlated negatively with aging index (p-value = 0.003), and positively with public transportation per capita (p-value = 0.012), the % of private long-term care hospital beds and, to a lesser extent (p-value = 0.070), the % of private acute care hospital beds (p-value = 0.006). CONCLUSION: Demographic and socioeconomic factors, and healthcare organization variables were found associated with a significant difference in the rate of COVID-19 spread in 36 provinces of Northern Italy. An aging population seemed to naturally contain social contacts. The availability of healthcare resources and their coordination could play an important part in spreading infection.

Estimation of direct costs of melanoma in the Veneto Region: a budget assessment and cost-consequence analysis.

BACKGROUND: While many evidence-based pathways have been introduced to drive quality improvements in cancer care, most of these do not include evidence about their affordability. The main aim of this study was to provide an estimation of the overall budget to cover all the needs of melanoma patients in Veneto Region, managed according to the clinical pathway defined by the Rete Oncologica Veneta. A second objective is to conduct a cost-consequence analysis, comparing two different treatments. METHODS: A very detailed whole-disease model was developed describing the patient's pathway from diagnosis through the first year of follow-up. Each procedure involved in the model was associated with a likelihood measure and a cost. The model can be used to estimate the expected direct costs associated with melanoma. RESULTS: We can observe that 0 and I stage, despite accounting for a huge percentage of new melanoma cases are characterized by a small percentage of the total costs. Stage III can be considered as the most expensive stage accounting for 54% of the total costs with a 12% of patients. Finally, the stage IV patients, although very few accounts for almost the 7% of the total costs. Regarding the cost-consequence analysis, it was estimated that the therapies introduced in 2016 led to an approximately 14% increase in the total costs. CONCLUSIONS: Modeling a clinical pathway with a high level of detail enables to identify the main sources of spending. The consequent analysis can thus help policymakers to plan the future resources allocation.

Cost-effectiveness of a melanoma screening programme using whole disease modelling.

OBJECTIVE: To assess the potential impact of a melanoma screening programme, compared with usual care, on direct costs and life expectancy in the era of targeted drugs and cancer immunotherapy. METHODS: Using a Whole Disease Model approach, a Markov simulation model with a time horizon of 25 years was devised to analyse the cost-effectiveness of a one-time, general practitioner-based melanoma screening strategy in the population aged over 20, compared with no screening. The study considered the most up-to-date drug therapy and was conducted from the perspective of the Veneto regional healthcare system within the Italian National Health Service. Only direct costs were considered. Sensitivity analyses, both one-way and probabilistic, were performed to identify the parameters with the greatest impact on cost-effectiveness, and to assess the robustness of our model. RESULTS: Over a 25-year time horizon, the screening intervention dominated usual care. The probabilistic sensitivity analyses confirmed the robustness of these findings. The key drivers of the model were the proportion of melanomas detected by the screening procedure and the adherence of the target population to the screening programme. CONCLUSIONS: The screening programme proved to be a dominant option compared with usual care. These findings should prompt serious consideration of the design and implementation of a regional or national melanoma screening strategy within a National Health Service.

Estimation of Direct Melanoma-related Costs by Disease Stage and by Phase of Diagnosis and Treatment According to Clinical Guidelines.

Cutaneous melanoma is a major concern in terms of healthcare systems and economics. The aim of this study was to estimate the direct costs of melanoma by disease stage, phase of diagnosis, and treatment according to the pre-set clinical guidelines drafted by the AIOM (Italian Medical Oncological Association). Based on the AIOM guidelines for malignant cutaneous melanoma, a highly detailed decision-making model was developed describing the patient's pathway from diagnosis through the subsequent phases of disease staging, surgical and medical treatment, and follow-up. The model associates each phase potentially involving medical procedures with a likelihood measure and a cost, thus enabling an estimation of the expected costs by disease stage and clinical phase of melanoma diagnosis and treatment according to the clinical guidelines. The mean per-patient cost of the whole melanoma pathway (including one year of follow-up) ranged from €149 for stage 0 disease to €66,950 for stage IV disease. The costs relating to each phase of the disease's diagnosis and treatment depended on disease stage. It is essential to calculate the direct costs of managing malignant cutaneous melanoma according to clinical guidelines in order to estimate the economic burden of this disease and to enable policy-makers to allocate appropriate resources.