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Background/purpose: To quantify savings of loss-of-QALE (quality-adjusted life expectancy) and lifetime medical costs from prevention of different cancers., Methods: We collected nation-wide data on 808,700 new cancer cases of 14 different organ systems and followed them from 1998 to 2014 in Taiwan. We also collected 13,005 cancer patients from a medical center and 47,320 repeated measurements of quality of life (QoL) of EQ-5D to obtain utility values and multiplied them with the corresponding survival rates to calculate QALE. With Kaplan-Meier estimation to survival function to the end of follow-up, we extrapolated to lifetime through a rolling over algorithm on the logit transform of the survival ratio between the index cohort and age-, sex, and calendar year matched referents simulated from vital statistics. Lifetime costs for each cancer were estimated by multiplying survival with average monthly costs after adjustment with annual discount rate. The loss-of-QALE was estimated by the difference in QALE between the index cancer cohort and corresponding referents., Results: The dynamic changes and weighted averages of the QoL utility values of 14 different cancers ranged from 0.82 to 0.95. Successful prevention of liver, lung, esophagus, or nasopharynx cancer would save more than 10 quality-adjusted life years and more than 21,000 USD per case for both genders. Since the saving of loss-of-QALE was adjusted for different age, sex, and calendar-year distributions, it could be used in cost effectiveness evaluation., Conclusion: Savings of loss-of-QALE and lifetime costs could be used for comparison of prevention, diagnosis, treatment and rehabilitation from a lifetime horizon., Competing Interests: Declaration of competing interest The authors have no conflicts of interest relevant to this article., (Copyright © 2021. Published by Elsevier B.V.)

Background: Quality of life (QoL) is important for clinicians to evaluate how cancer survivors judge their sense of well-being, and WHOQOL-BREF may be a good tool for clinical use. However, at least three issues remain unresolved: (1) the psychometric properties of the WHOQOL-BREF for cancer patients are insufficient; (2) the scoring method used for WHOQOL-BREF needs to be clarify; (3) whether different types of cancer patients interpret the WHOQOL-BREF similarly., Methods: We recruited 1000 outpatients with head/neck cancer, 1000 with colorectal cancer, 965 with liver cancer, 1438 with lung cancer and 1299 with gynecologic cancers in a medical center. Data analyses included Rasch models, confirmatory factor analysis (CFA), and Pearson correlations., Results: The mean WHOQOL-BREF domain scores were between 13.34 and 14.77 among all participants. CFA supported construct validity; Rasch models revealed that almost all items were embedded in their expected domains and were interpreted similarly across five types of cancer patients; all correlation coefficients between Rasch scores and original domain scores were above 0.9., Conclusion: The linear relationship between Rasch scores and domain scores suggested that the current calculations for domain scores were applicable and without serious bias. Clinical practitioners may regularly collect and record the WHOQOL-BREF domain scores into electronic health records., (Copyright © 2018. Published by Elsevier B.V.)

The study examined whether the items of the World Health Organization Quality of Life-Brief questionnaire can assess its four underlying domains (Physical, Psychological, Social, and Environment) in a sample of lung cancer patients. All patients ( n = 1150) were recruited from a medical center in Tainan, and each participant completed the World Health Organization Quality of Life-Brief. Several Rasch rating scale models were used to examine the data-model fit, and Rasch analyses corroborated that each domain of the World Health Organization Quality of Life-Brief could be unidimensional. Although three items were found to have a poor fit, all the other items fit the unidimensionality with ordered thresholds.

Purpose: This study attempted to compare changes in the Quality-of-Life (QoL) scores after three different first-line anti-cancer treatments for advanced non-small cell lung cancer (NSCLC) in a real-world clinical setting., Patients and Methods: From May 2011 to December 2013, we prospectively measured the QoL scores of patients with locally advanced or metastatic NSCLC using the World Health Organization Quality-of-Life-Brief (WHOQOL-BREF) questionnaire. Each QoL measurement was matched by age and sex with one healthy referent from the National Health Interview Survey. Dynamic changes in patients' QoL scores and major determinants were repeatedly assessed by construction of a mixed-effects model to adjust for possible confounders., Results: A total of 336 patients with 577 QoL measurements related to first-line anti-cancer treatments were enrolled. Performance status was the most important predictor of QoL scores in all domains after controlling for potential confounders. With age- and sex-matched healthy subjects as the reference, patients treated with gemcitabine + platinum showed significantly lower scores in multiple physical and psychological domain items in the WHOQOL-BREF. However, pemetrexed + platinum and gefitinib/erlotinib affected patients' QoL scores in 'energy/fatigue' and 'daily activities' with smaller magnitudes, and the scores appeared to improve after 3-4 months of treatment., Conclusions: Patients receiving gemcitabine + platinum as first-line anti-cancer treatment for advanced NSCLC experienced relatively poor QoL scores throughout treatment course. Studies to develop a real-time computerized system automatically updating the mixed-effects model for QoL to facilitate participatory clinical decision making by physicians, patients, and their families merit further research.

Objectives: This study attempts to quantify the difference in loss of quality-adjusted life expectancy (QALE) for patients with operable and inoperable non-small-cell lung cancer (NSCLC)., Patients and Methods: A cohort consisting of 1652 pathologically verified NSCLC patients with performance status 0-1 was monitored for 7 years (2005-2011) to obtain the survival function. This was further extrapolated to lifetime, based on the survival ratios between patients and age- and sex-matched referents simulated from the life tables of the National Vital Statistics of Taiwan. Between 2011 and 2012, EuroQol 5-dimension questionnaires were used to prospectively measure the quality-of-life (QoL) of a 518 consecutive, cross-sectional subsample. We adjusted the lifetime survival function by the utility values of QoL for the cancer cohort to obtain the QALE, while that for the age and sex-matched referents were adjusted to the values collected from the 2009 National Health Interview Survey, and the difference between them was the loss-of-QALE., Results: The QALE for patients with operable and inoperable NSCLC were 11.66±0.18 and 1.43±0.05 quality-adjusted life year (QALY), with the corresponding loss-of-QALE of 5.25±0.18 and 14.24±0.05 QALY, respectively. The lifetime utility difference for patients with operable and inoperable NSCLC was 9.00±0.18 QALY, after adjustment for QoL and lead-time bias., Conclusion: The utility gained from surgical operation for operable lung cancer is substantial, even after adjustment for lead-time bias. Future studies should compare screening programs with treatment strategies when carrying out cost-utility assessments to improve patients' values., (Copyright © 2014 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.)

Curative technologies improve patient's survival and/or quality of life but increase financial burdens. Effective prevention benefits all three. We summarize estimation methods and provide examples of how much money is spent per quality-adjusted life year (QALY) or life year (LY) on treating a catastrophic illness under a lifetime horizon and how many QALYs/LYs and lifetime medical costs (LMC) could be potentially saved by prevention. We established cohorts by interlinkages of Taiwan's nation-wide databases including National Health Insurance. We developed methods to estimate lifetime survival functions, which were multiplied with the medical costs and/or quality of life and summed up to estimate LMC, quality-adjusted life expectancy (QALE) and lifetime average cost per QALY/LY for catastrophic illnesses. By comparing with the age-, sex-, and calendar year-matched referents simulated from vital statistics, we obtained the loss-of-QALE and loss-of-life expectancy (LE). The lifetime cost-effectiveness ratios of ventilator-dependent comatose patients, dialysis, spinal cord injury, major trauma, and cancers were US$ 96,800, 16,200–20,000, 5500–5,900, 3400–3,600, and 2900–11,900 per QALY or LY, respectively. The successful prevention of lung, liver, oral, esophagus, stomach, nasopharynx, or ovary cancer would potentially save US$ 28,000–97,000 and > 10 QALYs; whereas those for end-stage kidney disease, stroke, spinal injury, or major trauma would be US$ 55,000–300,000 and 10–14 QALYs. Loss-of-QALE and loss-of-LE were less confounded indicators for comparing the lifetime health benefits of different technologies estimated from real-world data. Integration of prevention with treatment for resources allocation seems feasible and would improve equity and efficiency. [ABSTRACT FROM AUTHOR]

Background: Three different tyrosine kinase inhibitors have been approved as first-line therapies for epidermal growth factor receptor (EGFR) mutation-positive advanced non-small-cell lung cancer with similar overall survival. This study determined dynamic changes in quality of life (QoL) for patients using these therapies after controlling for potential confounders. Methods: From 2011 to 2016, we prospectively assessed the utility values and QoL scores of patients using the EuroQol five-dimension and World Health Organization Quality-of-Life – Brief questionnaires. QoL functions after initiation of treatment were estimated using a kernel-smoothing method. Dynamic changes in major determinants were repeatedly assessed for constructing mixed models. Results: A total of 344 patients were enrolled, with 934 repeated assessments. After controlling for performance status, disease progression, EGFR mutation subtype and other confounders, the mixed models showed significantly lower QoL scores for afatinib versus gefitinib in the physical, psychological and social domains, and 10 facets. The differences seemed to appear 10 months after initiation of treatment. In contrast, there was no significant difference between erlotinib and gefitinib in the scores of all domains and facets. Conclusion: QoL in patients receiving afatinib seemed to be lower than in those receiving gefitinib. Since the sample sizes in this study were relatively small, more studies are warranted to corroborate these results. [ABSTRACT FROM AUTHOR]