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      Quality of Life and Mortality of Long-Term Colorectal Cancer Survivors in the Seattle Colorectal Cancer Family Registry

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      PLoS ONE

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          Abstract

          Background and Aim

          Because most colorectal cancer patients survive beyond five years, understanding quality of life among these long-term survivors is essential to providing comprehensive survivor care. We sought to identify personal characteristics associated with reported quality of life in colorectal cancer survivors, and sub-groups of survivors potentially vulnerable to very low quality of life.

          Methods

          We assessed quality of life using the Veterans RAND 12-item Health Survey within a population-based sample of 1,021 colorectal cancer survivors in the Seattle Colorectal Cancer Family Registry, approximately 5 years post-diagnosis. In this case-only study, mean physical component summary scores and mental component summary scores were examined with linear regression. To identify survivors with substantially reduced ability to complete daily tasks, logistic regression was used to estimate odds ratios for “very low” summary scores, defined as a score in the lowest decile of the reference US population. All cases were followed for vital status following QoL assessment, and mortality was analyzed with Cox proportional hazards regression.

          Results

          Lower mean physical component summary score was associated with older age, female sex, obesity, smoking, and diabetes or other co-morbidity; lower mean mental component summary score was associated with younger age and female sex. Higher odds of very low physical component summary score was associated with older age, obesity, less education, smoking, co-morbidities, and later stage at diagnosis; smoking was associated with higher odds of very low mental component summary score. A very low physical component score was associated with higher risk of mortality (hazard ratio (95% confidence interval): 3.97 (2.95–5.34)).

          Conclusions

          Our results suggest that identifiable sub-groups of survivors are vulnerable to very low physical components of quality of life, decrements that may represent meaningful impairment in completing everyday tasks and are associated with higher risk of death.

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          Most cited references 40

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          A 12-Item Short-Form Health Survey: construction of scales and preliminary tests of reliability and validity.

          Regression methods were used to select and score 12 items from the Medical Outcomes Study 36-Item Short-Form Health Survey (SF-36) to reproduce the Physical Component Summary and Mental Component Summary scales in the general US population (n=2,333). The resulting 12-item short-form (SF-12) achieved multiple R squares of 0.911 and 0.918 in predictions of the SF-36 Physical Component Summary and SF-36 Mental Component Summary scores, respectively. Scoring algorithms from the general population used to score 12-item versions of the two components (Physical Components Summary and Mental Component Summary) achieved R squares of 0.905 with the SF-36 Physical Component Summary and 0.938 with SF-36 Mental Component Summary when cross-validated in the Medical Outcomes Study. Test-retest (2-week)correlations of 0.89 and 0.76 were observed for the 12-item Physical Component Summary and the 12-item Mental Component Summary, respectively, in the general US population (n=232). Twenty cross-sectional and longitudinal tests of empirical validity previously published for the 36-item short-form scales and summary measures were replicated for the 12-item Physical Component Summary and the 12-item Mental Component Summary, including comparisons between patient groups known to differ or to change in terms of the presence and seriousness of physical and mental conditions, acute symptoms, age and aging, self-reported 1-year changes in health, and recovery for depression. In 14 validity tests involving physical criteria, relative validity estimates for the 12-item Physical Component Summary ranged from 0.43 to 0.93 (median=0.67) in comparison with the best 36-item short-form scale. Relative validity estimates for the 12-item Mental Component Summary in 6 tests involving mental criteria ranged from 0.60 to 107 (median=0.97) in relation to the best 36-item short-form scale. Average scores for the 2 summary measures, and those for most scales in the 8-scale profile based on the 12-item short-form, closely mirrored those for the 36-item short-form, although standard errors were nearly always larger for the 12-item short-form.
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            Colorectal cancer statistics, 2014.

            Colorectal cancer is the third most common cancer and the third leading cause of cancer death in men and women in the United States. This article provides an overview of colorectal cancer statistics, including the most current data on incidence, survival, and mortality rates and trends. Incidence data were provided by the National Cancer Institute's Surveillance, Epidemiology, and End Results program and the North American Association of Central Cancer Registries. Mortality data were provided by the National Center for Health Statistics. In 2014, an estimated 71,830 men and 65,000 women will be diagnosed with colorectal cancer and 26,270 men and 24,040 women will die of the disease. Greater than one-third of all deaths (29% in men and 43% in women) will occur in individuals aged 80 years and older. There is substantial variation in tumor location by age. For example, 26% of colorectal cancers in women aged younger than 50 years occur in the proximal colon, compared with 56% of cases in women aged 80 years and older. Incidence and death rates are highest in blacks and lowest in Asians/Pacific Islanders; among males during 2006 through 2010, death rates in blacks (29.4 per 100,000 population) were more than double those in Asians/Pacific Islanders (13.1) and 50% higher than those in non-Hispanic whites (19.2). Overall, incidence rates decreased by approximately 3% per year during the past decade (2001-2010). Notably, the largest drops occurred in adults aged 65 and older. For instance, rates for tumors located in the distal colon decreased by more than 5% per year. In contrast, rates increased during this time period among adults younger than 50 years. Colorectal cancer death rates declined by approximately 2% per year during the 1990s and by approximately 3% per year during the past decade. Progress in reducing colorectal cancer death rates can be accelerated by improving access to and use of screening and standard treatment in all populations. © 2014 American Cancer Society, Inc.
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              Cross-validation of item selection and scoring for the SF-12 Health Survey in nine countries: results from the IQOLA Project. International Quality of Life Assessment.

              Data from general population surveys (n = 1483 to 9151) in nine European countries (Denmark, France, Germany, Italy, the Netherlands, Norway, Spain, Sweden, and the United Kingdom) were analyzed to cross-validate the selection of questionnaire items for the SF-12 Health Survey and scoring algorithms for 12-item physical and mental component summary measures. In each country, multiple regression methods were used to select 12 SF-36 items that best reproduced the physical and mental health summary scores for the SF-36 Health Survey. Summary scores then were estimated with 12 items in three ways: using standard (U.S.-derived) SF-12 items and scoring algorithms; standard items and country-specific scoring; and country-specific sets of 12 items and scoring. Replication of the 36-item summary measures by the 12-item summary measures was then evaluated through comparison of mean scores and the strength of product-moment correlations. Product-moment correlations between SF-36 summary measures and SF-12 summary measures (standard and country-specific) were very high, ranging from 0.94-0.96 and 0.94-0.97 for the physical and mental summary measures, respectively. Mean 36-item summary measures and comparable 12-item summary measures were within 0.0 to 1.5 points (median = 0.5 points) in each country and were comparable across age groups. Because of the high degree of correspondence between summary physical and mental health measures estimated using the SF-12 and SF-36, it appears that the SF-12 will prove to be a practical alternative to the SF-36 in these countries, for purposes of large group comparisons in which the focus is on overall physical and mental health outcomes.
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                Author and article information

                Affiliations
                Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA, United States of America
                Iranian Institute for Health Sciences Research, ACECR, ISLAMIC REPUBLIC OF IRAN
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Conceived and designed the experiments: RC SVA. Performed the experiments: SVA. Analyzed the data: SVA. Contributed reagents/materials/analysis tools: PAN. Wrote the paper: SVA RC PAN. Manuscript revision: PAN RC SVA. Interpretation of results: PAN RC SVA.

                Contributors
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                2 June 2016
                2016
                : 11
                : 6
                27253385 4890809 10.1371/journal.pone.0156534 PONE-D-15-32462
                © 2016 Adams et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                Counts
                Figures: 2, Tables: 3, Pages: 13
                Product
                Funding
                Funded by: funder-id http://dx.doi.org/10.13039/100000054, National Cancer Institute;
                Award ID: UM1 CA167551
                Funded by: funder-id http://dx.doi.org/10.13039/100000054, National Cancer Institute;
                Award ID: U01CA074794
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/100000054, National Cancer Institute;
                Award ID: K05 CA152715
                Award Recipient :
                This work was supported by the National Cancer Institute, National Institutes of Health grant UM1 CA167551 to R.M. Haile to support the Colorectal Cancer Family Registry Cohort infrastructure, grant U01CA074794 to P. A. Newcomb to support the Seattle Colorectal Cancer Family Registry, and grant K05 CA152715 to P. A. Newcomb. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Medicine and Health Sciences
                Oncology
                Cancers and Neoplasms
                Colorectal Cancer
                Medicine and Health Sciences
                Oncology
                Cancer Detection and Diagnosis
                Medicine and Health Sciences
                Health Care
                Quality of Life
                Medicine and Health Sciences
                Endocrinology
                Endocrine Disorders
                Diabetes Mellitus
                Medicine and Health Sciences
                Metabolic Disorders
                Diabetes Mellitus
                People and Places
                Demography
                Death Rates
                Biology and Life Sciences
                Population Biology
                Population Metrics
                Death Rates
                Medicine and Health Sciences
                Diagnostic Medicine
                Diabetes Diagnosis and Management
                Biology and Life Sciences
                Physiology
                Physiological Parameters
                Body Weight
                Obesity
                Medicine and Health Sciences
                Physiology
                Physiological Parameters
                Body Weight
                Obesity
                Research and Analysis Methods
                Mathematical and Statistical Techniques
                Statistical Methods
                Regression Analysis
                Linear Regression Analysis
                Physical Sciences
                Mathematics
                Statistics (Mathematics)
                Statistical Methods
                Regression Analysis
                Linear Regression Analysis
                Custom metadata
                Due to ethical restrictions regarding patient privacy and consent, data are available upon request. Requests for the data may be sent to either Ms. Rachel Malen ( rmalen@ 123456fredhutch.org ) and Ms. Allyson Templeton ( atemplet@ 123456fredhutch.org ), or to author Dr. Newcomb ( pnewcomb@ 123456fredhutch.org ).

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