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The objective of this study was to estimate the association between SF-12v2® Health Survey (SF-12v2) scores and subsequent health care resource utilization (HCRU) among patients with cancer.
We analyzed 18+ year participants in the Medical Expenditure Panel Survey, diagnosed with active cancer or malignancy (n = 647). HCRU was measured by total medical expenditures (MEs) and number of medical events (EVs) in the 6 months following the SF-12v2 assessment. The effect of SF-12v2 scores (physical (PCS) and mental (MCS) component summary scores and the SF-6D health-utility score) on HCRU was estimated using generalized linear models. Estimates were obtained for the entire sample and for the four cancer groups present in the sample: breast, prostate, skin, and lung.
For PCS and MCS, a one-point better score was associated with 2% lower MEs (P < 0.001) and 2.5% lower MEs (P = 0.015), respectively. A 0.05-point better SF-6D score was associated with 7% lower MEs (P = 0.003). PCS and SF-6D were more strongly associated with MEs for prostate cancer patients (P = 0.009 and P = 0.003) and PCS was more strongly associated with MEs for skin cancer patients (P = 0.019), compared to other cancer groups. A 1-point better PCS predicted 1% lower EVs, while a 0.05 better SF-6D score predicted 4% lower EVs.
The significant associations between SF-12v2 scores from oncology patients and subsequent HCRU can guide interpretations of SF-12v2 scores in evaluation of therapies and in health policy decisions.
Agency for Healthcare Research and Quality. (2017). Total expenses and percent distribution for selected conditions by type of service: United States, 2014. Medical expenditure panel survey household component data. Generated interactively (November 22, 2017).
Yabroff, K. R., Lund, J., Kepka, D., & Mariotto, A. (2011). Economic burden of cancer in the United States: Estimates, projections, and future research. Cancer Epidemiology, Biomarkers & Prevention. https://doi.org/10.1158/1055-9965.EPI-11-0650. CrossRef
Zagadailov, E., Fine, M., & Shields, A. (2013). Patient-reported outcomes are changing the landscape in oncology care: Challenges and opportunities for payers. American Health & Drug Benefits, 6(5), 264–274.
King, S., Exley, J., Parks, S., Ball, S., Bienkowska-Gibbs, T., MacLure, C., et al. (2016). The use and impact of quality of life assessment tools in clinical care settings for cancer patients, with a particular emphasis on brain cancer: Insights from a systematic review and stakeholder consultations. Quality of Life Research. https://doi.org/10.1007/s11136-016-1278-6. CrossRefPubMedPubMedCentral
Snyder, C. F., Smith, K. C., Bantug, E. T., Tolbert, E. E., Blackford, A. L., & Brundage, M. D. (2017). What do these scores mean? Presenting patient-reported outcomes data to patients and clinicians to improve interpretability. Cancer. https://doi.org/10.1002/cncr.30530. CrossRefPubMedPubMedCentral
Sztankay, M., Giesinger, J. M., Zabernigg, A., Krempler, E., Pall, G., Hilbe, W., et al. (2017). Clinical decision-making and health-related quality of life during first-line and maintenance therapy in patients with advanced non-small cell lung cancer (NSCLC): Findings from a real-world setting. BMC Cancer. https://doi.org/10.1186/s12885-017-3543-7. CrossRefPubMedPubMedCentral
Barbera, L., Atzema, C., Sutradhar, R., Seow, H., Howell, D., Husain, A., et al. (2013). Do patient-reported symptoms predict emergency department visits in cancer patients? A population-based analysis. Annals of Emergency Medicine. https://doi.org/10.1016/j.annemergmed.2012.10.010. CrossRefPubMed
Doll, K. M., Snavely, A. C., Kalinowski, A., Irwin, D. E., Bensen, J. T., Bae-Jump, V., et al. (2014). Preoperative quality of life and surgical outcomes in gynecologic oncology patients: A new predictor of operative risk? Gynecologic Oncology. https://doi.org/10.1016/j.ygyno.2014.04.002. CrossRefPubMedPubMedCentral
Wagner-Johnston, N. D., Carson, K. A., & Grossman, S. A. (2010). High outpatient pain intensity scores predict impending hospital admissions in patients with cancer. Journal of Pain and Symptom Management. https://doi.org/10.1016/j.jpainsymman.2009.06.012. CrossRefPubMed
Bingener, J., Sloan, J. A., Novotny, P. J., Pockaj, B. A., & Nelson, H. (2015). Perioperative patient-reported outcomes predict serious postoperative complications: A secondary analysis of the COST trial. Journal of Gastrointestinal Surgery. https://doi.org/10.1007/s11605-014-2613-2. CrossRefPubMedPubMedCentral
Hall, P. S., Hamilton, P., Hulme, C. T., Meads, D. M., Jones, H., Newsham, A., et al. (2015). Costs of cancer care for use in economic evaluation: A UK analysis of patient-level routine health system data. British Journal of Cancer. https://doi.org/10.1038/bjc.2014.644. CrossRefPubMedPubMedCentral
Brazier, J. E., & Roberts, J. (2004). The estimation of a preference-based measure of health from the SF-12. Medical Care, 42(9), 851–859. CrossRef
Agency for Healthcare Research and Quality. (2017). Medical Expenditure Panel Survey (MEPS). Accessed November, 22, 2017, from https://meps.ahrq.gov/mepsweb.
Maruish, M. E. (Ed.). (2012). User’s manual for the SF-12v2 health survey (3rd ed.). Lincoln: QualityMetric Inc.
Bellardita, L., Damiano, R., Porpiglia, F., Scattoni, V., Amodeo, A., Bortolus, R., et al. (2016). Adaptation and validation of an Italian version of the Prostate Cancer Specific Quality of Life Instrument (PROSQOLI). European Review for Medical and Pharmacological Sciences, 20, 2773–2778. PubMed
Durá-Ferrandis, E., Mandelblatt, J. S., Clapp, J., Luta, G., Faul, L., Kimmick, G., et al. (2017). Personality, coping, and social support as predictors of long-term quality-of-life trajectories in older breast cancer survivors: CALGB protocol 369901 (Alliance). Psycho-oncology. https://doi.org/10.1002/pon.4404. CrossRefPubMedPubMedCentral
Larsen, T., Hausken, T., Otteraaen Ystad, S., Hovdenak, N., Mueller, B., & Lied, G. A. (2017). Does the low FODMAP diet improve symptoms of radiation-induced enteropathy? A pilot study. Scandinavian Journal of Gastroenterology. https://doi.org/10.1080/00365521.2017.1397186. CrossRefPubMed
de Oliveira A. L., Mendes, L. L., Netto, M. P., & Leite, I. C. G. (2017). Cross-cultural adaptation and validation of the stoma quality of life questionnaire for patients with a colostomy or ileostomy in Brazil: A cross-sectional Study. Ostomy Wound Manage, 63, 34–41.
Lopez, G., McQuade, J., Cohen, L., Williams, J. T., Spelman, A. R., Fellman, B., et al. (2017). Integrative oncology physician consultations at a comprehensive cancer center: Analysis of demographic, clinical and patient reported outcomes. Journal of Cancer. https://doi.org/10.7150/jca.17506. CrossRefPubMedPubMedCentral
Scheltema, M. J., van den Bos, W., Siriwardana, A. R., Kalsbeek, A. M., Thompson, J. E., Ting, F., et al. (2017). Feasibility and safety of focal irreversible electroporation as salvage treatment for localized radio-recurrent prostate cancer. BJU International. https://doi.org/10.1111/bju.13991. CrossRefPubMed
Manning, W. G., & Mullahy, J. (2001). Estimating log models: To transform or not to transform? Journal of Health Economics, 20, 461–494. CrossRef
Manning, W. G., Basu, A., & Mullahy, J. (2003). Generalized modeling approaches to risk adjustment of skewed outcomes data. NBER Technical Working Paper, Cambridge, MA.
Fragoso, C. A. V., Murphy, T. E., Agogo, G. O., Allore, H. G., & McAvay, G. J. (2017). Asthma-COPD overlap syndrome in the US: A prospective population-based analysis of patient-reported outcomes and health care utilization. International Journal of Chronic Obstructive Pulmonary Disease. https://doi.org/10.2147/COPD.S121223. CrossRef
Singh, J., Pokhrel, S., & Longworth, L. (2018). Can social care needs and well-being be explained by the EQ-5D? Analysis of the health survey for England. Value in Health. https://doi.org/10.1016/j.jval.2018.01.002. CrossRefPubMed
Yu, W. W., & Machlin, S. R. (2005). An examination of skewed health expenditure data from the Medical Expenditure Panel Survey (MEPS). Journal of Economic and Social Measurement, 30(2), 127–134.
- Health-related quality of life predicted subsequent health care resource utilization in patients with active cancer
Jakob Bue Bjorner
- Springer International Publishing
Quality of Life Research
An International Journal of Quality of Life Aspects of Treatment, Care and Rehabilitation - Official Journal of the International Society of Quality of Life Research
Print ISSN: 0962-9343
Elektronisch ISSN: 1573-2649