A811standardized the oncology treatment fields available in the specific oncology database (DataSUS AQ). Standardization included harmonization of different names used for the same drug name (i.e., cetuximab, cetux, cetukimabe and ketuxim), including generic and brand names. We also converted acronyms use in NCCN and MOC Brazil guidelines to the generic name (i.e.: fluoracil and 5FU; irinotecan and CPT-11). We created a new standardized table with additional fields (regimen name, drugs used, adjuvant therapy and a high/low cost flag). For this analysis we filtered by APAC (High complexity procedures approval) code for colorectal cancer (CRC) and lung cancer (LC) from 2012 to 2014. All blank or not identified regimens were excluded from this analysis. The final sample was composed by 50,729 CRC and 23,525 LC records. Results: It was compared the total number of regimens available at raw data and those standardized. Regarding CRC regimens we found 7,698 different treatments in the raw database and 82 in the standardized dataset, a considerable reduction. In raw data, the most frequent regimen was FOLFOX representing 7.9% of all records, in contrast to standardized dataset where FOLFOX regimen represented 33.6% of all records. We found 262 records written in different ways in the raw database that referred to FOLFOX. Analyzing LC records, the most frequent regimen in raw data was carboplatin+taxo representing 3.1% of LC APACs claims in comparison to the standardized dataset where carboplatin+taxol represented 27.6% of all claims; 278 raw records had different names referring to carboplatin+taxol. ConClusions: DataSUS can be a reliable source on oncology consumption therapies after standardizing data fields that were originally introduced by manual typing.
Objectives: Budget impact and cost-effectiveness analysis are often required by payers when discussing drug reimbursement. We hereby present a cost-minimization (CMA) and budget impact analysis (BIA) regarding the incorporation of certolizumab pegol (CZP) for the treatment of patients with Crohn's disease, a debilitating condition that affects the digestive tract. Methods: Considering that the scientific literature demonstrates CZP as effective as the alternatives (infliximab and adalimumab), a CMA was conducted, including a Markov 10-year time horizon modeling. Focusing on the assumptions for both CMA and BIA, a total of 36 stakeholders from the private sector were surveyed regarding treatment and disease-related costs. For the BIA, drug acquisition costs, administration costs, no population growth and an immunobiologic drug (bDMARD) switching rate of 5% were also considered. We assumed that CZP would gradually gain market share until it reaches 20% of new or switching patients in the fourth year. In addition, probability sensitivity analyses were performed. Results: In the cost-minimization, the calculated costs for 10-year treatment were BRL149k (infliximab); BRL118k (adalimumab) and BRL83k (CZP). Probabilistic sensitivity analysis was conducted with 1,000 random simulations, with CZP being less costly than its comparators in all simulations. Additionally, the BIA result indicates that CZP is a cost-saving intervention, with a predicted five-year impact of BRL317k for every 100-patient cohort. Conclusions: Certolizumab pegol was shown to be not only effective but also a cost-saving drug when compared to other anti-TNF drugs available for the Brazilian private healthcare system.
RESUMOObjetivos: Análises de impacto orçamentário e de custo-efetividade são, com frequência, exigidas por pagadores para a decisão sobre incorporação de drogas. Por esse motivo, apresentaremos uma análise de custo-minimização e de impacto orçamentário do certolizumabe pegol (CZP) para o tratamento de pacientes com doença de Crohn, doença crônica e debilitante que afeta o trato digestivo. Métodos: Trinta e seis pagadores privados foram entrevistados para que fosse possível
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