An Application of Quah and Vahey’s SVAR Methodology for Estimating Core Inflation in India: A Note

Inflation, calculated as year-on-year per cent change in general price level, represents a combined effect of several types of price changes. The monetary authorities primarily focus to track that part of inflation, which can be effectively monitored and controlled using various monetary instruments. This persistent component of inflation is termed as ‘Core Inflation’, which possesses long-run properties as well as predictive power to forecast inflation. This paper makes use of Quah and Vahey’s definition of core inflation as that component of headline inflation, which has no impact on output in medium to long run and estimates it by placing restrictions on vector auto regression system with inflation and output growth. The analysis is based on monthly data from April 1995 to January 2009. Empirical results showed that in India, during 2006 and 2007, the inflation process was stronger than what headline inflation figures actually depicted and in 2008 the inflationary process has tended to be somewhat weaker than what was observed in headline inflation.

     

Converting EORTC QLQ-C30 scores to utility scores in the brigatinib ALTA study

Abstract

Aims: Health utilities summarize a patient’s overall health status. This study estimated utilities based on the European Organization for Research and Treatment of Cancer Quality of Life Questionnaire Core-30 (QLQ-C30), a widely used measure of health-related quality-of-life (HRQoL) in oncology, using published mapping algorithms.

Materials and methods: Data were from the Anaplastic Lymphoma Kinase (ALK) in Lung Cancer Trial of brigatinib (ALTA; NCT02094573), an open-label, international, phase 2 study. ALTA evaluated the efficacy and safety of two randomized dosing regimens of brigatinib in patients with locally advanced or metastatic ALK?+?non-small cell lung cancer (NSCLC) that had progressed on prior therapy with crizotinib. QLQ-C30 scores were mapped to European Quality-of-Life-5 Dimensions (EQ-5D) utility scores using two published algorithms (Khan et al. for EQ-5D-5L; Longworth et al. for EQ-5D-3L). The impact of brigatinib treatment on health utilities over time was assessed.

Results: The analysis included 208 subjects. Mean baseline utility scores for both algorithms ranged between 0.60???0.71 and increased to 0.78 by cycle 5. Utility improvements were sustained during most of the treatment, before disease progression. Minor variations were observed between utility scores; Khan et al. estimates were approximately 0.01 or 0.02 points lower than Longworth et al. estimates.

Limitations: Algorithms considered were limited to those available in the published literature at the time of the study. This utility analysis was exploratory, and the ALTA trial did not include an internal control group (i.e. standard of care) and was not powered to detect differences in QoL/utility outcomes between treatment arms.

Conclusions: Converting QLQ-C30 scores into utilities in trials using established mapping algorithms can improve evaluation of medicines from the patient perspective. Both algorithms suggested that brigatinib improved health utility in crizotinib-refractory ALK?+?NSCLC patients, and improvements were maintained during most of the treatment.

Clinicaltrials.gov identifier: NCT02094573