Beyond Measurement: Strengthening HRQOL Research in Cancer

We congratulate Snehapriya et al. [1] for their article "Unveiling Health-Related Quality of Life (HRQOL) and Sociodemographic Factors Predicting HRQOL among Cancer Patients in Eastern India," which offers valuable insights through a community-based study.However, certain concerns merit attention.Methodologically, using the English version of the EORTC QLQ-C30 tool without translation or cultural adaptation in a predominantly Odia-speaking population questions the validity and reliability of the collected data.At least face validity of Odia translated tool was desirable.A reader can infer from the statement ", the investigator visited..", that data was collected by a single investigator, but lack of further details such as knowledge of local language of investigator limits understanding of field implementation of the study.Symptom burden is a predictor of quality of life in cancer patients, which can be assessed using Memorial Symptom Assessment Scale (MSAS) [2].This study though reports use of individual symptom scales, use of MSAS could have offered wider and more nuanced picture of patients' symptom experiences, in turn, would have provided insights for clinical interventions to truly support cancer patients in their journey toward better health.The sample size formula provided by authors is for infinite population, while the cancer registry over a 1.5 year is a finite population.The authors have considered high (15%) margin of error to estimate the sample size.Considering, 2678 enrolment in the registry, a finite population correction, and lower margin of error, could have been considered.Participant recruitment from the Hospital-Based-Cancer-Registry (HBCR) at AIIMS Bhubaneswar between July 2021 -December 2022 raises feasibility concerns, especially for late enrollees, considering the time required for registry access, telephonic consent, and home interviews by the single investigator.In the statistical analysis parametric and nonparametric tests have been mentioned (ANOVA, t-test, Kruskal-Wallis, Mann-Whitney U), but their specific application is not clearly attributed in tables or text.Table 5, that tests association between Global Health Status and Sociodemographic Factors among Cancer Patients, used 'F' and 't' statistics signifying use of ANOVA and t tests, which are parametric tests only.The current study has no multivariate analysis, limiting our understanding