Abstract
Background
The number of head and neck cancer (HNC) survivors has been increasing due to improving survival in the United States. The aim of this study is to evaluate the incidence of respiratory disease diagnoses in HNC survivors compared to cancer free individuals. A second aim is to investigate risk factors for respiratory disease among HNC survivors.
Methods
HNC patients diagnosed from 1996 to 2012 were identified in the Utah Cancer Registry (n=1,901). Up to 5 cancer free individuals from the general population (n=7,769) were matched to each HNC survivor on birth year, sex, birth state, and follow up time. Electronic medical records and statewide healthcare facility data were used to identify disease diagnosis after cancer diagnosis. Cox proportional hazards models were used to estimate the risks of respiratory diseases.
Results
Median follow up times were 4.5 years for HNC survivors and 7.8 years for the general population cohort. The risks of respiratory infection (HR=1.63, 95%CI=1.40-1.90), chronic obstructive pulmonary diseases and bronchiectasis (COPD; HR=2.65, 95%CI=2.13-3.29), and aspiration pneumonitis (HR=6.21, 95%CI=3.98-9.68) were higher among HNC survivors compared with the general population cohort >5 years after cancer diagnosis. Age at diagnosis, baseline body mass index, sex, baseline smoking, treatment modality, primary site, and stage were associated with the risk of adverse respiratory outcomes among HNC survivors.
Conclusions
The risk of adverse respiratory outcomes among HNC survivors was much higher than among the general population cohort. Multidisciplinary care is needed to prevent the incidence of adverse respiratory outcomes among HNC survivors.
Keywords: Head and Neck Cancer, Cancer Survivor, Utah Cancer Survivorship Study, Adverse outcome, Respiratory system
Precis
In this study, we investigated that the risk of adverse respiratory outcomes among HNC survivors and observed that it was much higher than a matched general population cohort. Therefore, multidisciplinary care is needed to prevent the incidence of adverse respiratory outcomes among HNC survivors.
Introduction
In the United States, there were an estimated 48,000 men and 17,400 women diagnosed with head and neck cancer (HNC) in 2019, and it was the 8th most common cancer among men1. Advances in treatment modality have been improving survival for HNC over the last few decades2. Moreover, the incidence rate of oropharyngeal cancer associated with human papilloma virus (HPV) infection has been increasing 3 and HPV-positive oropharyngeal cancer has a better prognosis than HPV-negative oropharyngeal cancer 4. Indeed, 5-year survival rates have increased from 53% for head and neck cancer patients diagnosed between 1975 and 1977 to 68% for head and neck cancer patients diagnosed between 2008 and 2014 in the United States1. For these reasons, the number of HNC survivors has been increasing and the estimated number of HNC survivors is expected to increase from 229,900 in 2016 to 293,000 in 20262. Since head and neck regions are associated with mastication, swallowing, speaking and breathing, physicians need to consider organ preservation as well as clinical outcomes for HNC. Although non-surgical approaches have achieved clinical outcomes which are comparable with surgery together with organ preservation5-8, acute and late effects due to radiotherapy (RT) or chemotherapy (CT) are a concern9. In addition, smoking is an established risk factor for HNC10, 11, and we must consider smoking-related long term disease risks among HNC survivors.
The aim of this study is to investigate the risk of respiratory diseases compared with a general population in a population-based cohort of HNC survivors in Utah. A secondary aim is to investigate risk factors for respiratory diseases among HNC survivors.
Materials and Methods
The Utah Population Database (UPDB) links data from the Utah Cancer Registry, part of the Surveillance, Epidemiology, and End Results (SEER) Program registries, to electronic medical records (EMR), driver license, voter registration, genealogical data, and vital records. The UPDB consists of a single record for each individual with linkage across the multiple databases. We used the Utah Cancer Registry to identify cancer patients according to the inclusion criteria: (i) diagnosis with first primary HNC between 1996 and 2012 (subsites including oral cavity, oropharynx, hypopharynx, oral cavity or pharynx not specified (NOS), and larynx; ICD-O-3 C00.3-C00.9, C01.9, C02.0-C02.9, C03.0-C03.9, C04.0-C04.9, C05.0-C05.9, C06.0-C06.9, C09.0-C09.9, C10.0-C10.9, C12.9, C13.0-C13.9, C14.0-C14.8; C32.0–32.9) and (ii) age at diagnosis ≥18 years old. From 1996 to 2012, 2,186 first primary HNCs were diagnosed in Utah. We excluded 285 HNC patients with carcinoma in situ or missing disease stage, leaving 1,901 HNC patients for analysis. Each HNC patient was matched to 4–5 cancer-free individuals on birth year, birth state, sex, and the date of last residence in Utah (equal or later than case) from the UPDB. Four to five individuals from the general population who met the matching criterion for each head and neck cancer patient were randomly selected. Cancer-free individuals were thus alive at the time of the case’s cancer diagnosis.
Diseases of the respiratory system were assessed by linkage to EMR from the University of Utah Hospital and/or Intermountain Healthcare hospital system data warehouse (Intermountain), which provide treatment to 85–90% of cancer patients in Utah. We also linked statewide ambulatory surgery and inpatient hospital data to the HNC patients and the general population cohort.
The clinical and demographic characteristics of the HNC patients and the general population cohort were retrieved from the Utah Cancer Registry, the hospital EMR and the UPDB . Cancer treatment data was obtained from the Utah Cancer Registry for first course treatment. Vital status was available from death certificates and social security death index linkage. Additionally, baseline smoking status prior to cancer diagnosis (smoker/nonsmoker) was also available from the hospital EMR and statewide healthcare data. Body mass index (BMI) was calculated from the height and weight information from Driver’s License Division data linked to the UPDB. A specific query of the medical conditions was conducted using ICD-9 and CPT (current procedural terminology) codes (Supplemental table 1). We focused on conditions diagnosed after the HNC diagnosis for disease of the respiratory system, including respiratory infection, chronic obstructive pulmonary diseases and bronchiectasis (COPD), and aspiration pneumonitis. Respiratory infections include pneumonia, influenza, acute bronchitis and acute and chronic tonsillitis. To validate the disease diagnoses, we previously investigated concordance between self-report and EMR/statewide data for various diseases (n=221 cancer patients). For pneumonia, the sensitivity was 100% and specificity was 83.1%. We also identified tobacco smokers with the ICD-9 code for ‘tobacco use disorders’ 305.1, ICD-10 codes for nicotine dependence, and with CPT codes for tobacco cessation counseling based on the American Academy of Family Physicians coding guidelines. This study was approved by the University of Utah and Intermountain Healthcare IRBs.
Statistical analyses were conducted in SAS version 9. The aims of our analysis were to (1) compare the incidence rate of each respiratory disease between the HNC patients and the general population cohort, and estimate the corresponding hazard ratio (HR); and (2) estimate the HRs for clinical and demographic characteristics as potential risk factors for the respiratory diseases among HNC patients who survived at least 5 years after cancer diagnosis. The person-time at risk was defined as the start of the follow up (date of cancer diagnosis or date of study entry for cancer-free individuals) to the date of disease diagnosis, or death. Individuals were censored at the last known date of residence in Utah. The follow up started from 1996 and went up to June 2016. The last known date of residence in Utah was determined by whether the individual was observed in one of these records in Utah: birth certificate (for a child of the individual), marriage, divorce, voting records, driver’s license records and cancer registry. Individuals who were diagnosed with respiratory diseases before the date of cancer diagnosis or study entry were not included in the analysis for that specific outcome since they had a prevalent condition. Cox Proportional Hazards models with risk set stratification were used to estimate HRs comparing the risk of respiratory disease between the HNC patients and the general population cohort. We adjusted on baseline Charlson comorbidity index (CCI)31, race, and baseline BMI as potential confounders and stratified by age at diagnosis (<65 vs ≥65), sex (male vs female), race (white vs other), baseline CCI (0 vs ≥1), BMI at baseline (<18.5 kg/m2 vs ≥18.5 kg/m2 to <25 kg/m2 vs ≥25 kg/m2 to <30 kg/m2 vs ≥30 kg/m2), smoking status (nonsmoker vs smoker), treatment modality (surgery vs RT vs surgery+RT vs RT+CT vs surgery + RT + CT vs others), subsites (oral cavity vs oropharynx vs hypopharynx vs larynx vs NOS), and clinical disease stage (local vs regional vs distant).
Results
The majority of HNC patients were diagnosed between 50 and 69 years of age (Table 1). Most of the HNC patients had squamous cell carcinoma histology (90.2%); 42.4% were localized, 33.3% were oropharynx, and 33.7% received surgery alone for treatment modality. Compared to the general population cohort, HNC survivors had a higher proportion of whites, patients with lower BMI, younger age, and shorter follow-up period (Table 2). A greater proportion of HNC survivors had smoked before cancer diagnosis (28.0%) than the general population cohort (9.0%). Median follow up times were 4.5 years for HNC survivors and 7.8 years for the general population cohort.
Table 1.
Clinical characteristics of head and neck cancer survivors diagnosed in Utah between 1996 and 2012 (N=1901)
| Number | Percent | |
|---|---|---|
| Diagnosis year | ||
| 1996-2000 | 470 | 24.7 |
| 2001-2005 | 540 | 28.4 |
| 2006-2010 | 608 | 32.0 |
| 2011-2012 | 283 | 14.9 |
| Age at diagnosis | ||
| 20-49 | 333 | 17.5 |
| 50-59 | 544 | 28.6 |
| 60-69 | 548 | 28.8 |
| 70-79 | 330 | 17.4 |
| 80-95 | 146 | 7.7 |
| Cancer stage at diagnosis | ||
| Localized | 806 | 42.4 |
| Regional | 797 | 41.9 |
| Distant | 298 | 15.7 |
| Histology | ||
| SCC | 1715 | 90.2 |
| Non-SCC | 186 | 9.8 |
| Subsite | ||
| Oral cavity | 566 | 29.8 |
| Oropharynx | 633 | 33.3 |
| Hypopharynx | 89 | 4.7 |
| Larynx | 465 | 24.4 |
| NOS | 148 | 7.8 |
| Treatment modality | ||
| Surgery | 640 | 33.7 |
| Radiotherapy | 168 | 8.8 |
| Chemotherapy | 13 | 0.7 |
| Surgery+Radiotherapy | 397 | 20.9 |
| Radiotherapy+Chemotherapy | 310 | 16.3 |
| Surgery+Chemotherapy | 10 | 0.5 |
| Surgery+Radiotherapy+Chemotherapy | 213 | 11.2 |
| No treatment | 73 | 3.8 |
| Unknown | 77 | 4.1 |
Abbreviations; SCC, squamous cell carcinoma, NOS, oral cavity and pharynx not specified.
Table 2.
Characteristics of head and neck cancer patients diagnosed in Utah between 1996 and 2012 and the general population cohort
| Head and Neck Patients (N=1901) |
General population cohort (N=7796) |
|||
|---|---|---|---|---|
| N | % | N | % | |
| Birth year | ||||
| 1904-1919 | 78 | 4.1 | 310 | 4.0 |
| 1920-1929 | 233 | 12.2 | 843 | 10.8 |
| 1930-1939 | 427 | 22.5 | 1610 | 20.6 |
| 1940-1949 | 514 | 27.0 | 2126 | 27.3 |
| 1950-1959 | 450 | 23.7 | 1984 | 25.5 |
| 1960-1969 | 142 | 7.5 | 655 | 8.4 |
| 1970-1979 | 47 | 2.5 | 220 | 2.8 |
| 1980-1989 | 10 | 0.5 | 48 | 0.6 |
| Sex | ||||
| Male | 1401 | 73.7 | 5718 | 73.3 |
| Female | 500 | 26.3 | 2078 | 26.7 |
| Race | ||||
| White | 1845 | 97.1 | 7158 | 91.8 |
| Other | 56 | 2.9 | 638 | 8.2 |
| BMI at baseline (kg/m2) | ||||
| <18 | 21 | 1.1 | 32 | 0.4 |
| ≥18 to <25 | 814 | 42.8 | 2748 | 35.3 |
| ≥25 to <30 | 751 | 39.5 | 3352 | 43.0 |
| ≥30 | 315 | 16.6 | 1664 | 21.3 |
| Charlson Comorbidity Index | ||||
| 0 | 1150 | 60.5 | 5,508 | 70.7 |
| ≥1 | 751 | 39.5 | 2,288 | 29.4 |
| Age at the end of follow up (years) | ||||
| 27-59 | 520 | 27.3 | 1695 | 21.7 |
| 60-69 | 570 | 30.0 | 2362 | 30.3 |
| 70-79 | 485 | 25.5 | 2034 | 26.1 |
| 80-84 | 163 | 8.6 | 780 | 10.0 |
| 85-99 | 163 | 8.6 | 925 | 11.9 |
| Follow up period (years) | ||||
| 0-2 | 593 | 31.2 | 259 | 3.3 |
| 2-5 | 440 | 23.1 | 2081 | 26.7 |
| 5-10 | 500 | 26.3 | 2699 | 34.6 |
| 10-20 | 368 | 19.4 | 2757 | 35.4 |
| Median | 4.5 years | 7.8 years | ||
Abbreviation; BMI, body mass index.
The risk of adverse respiratory outcomes among HNC survivors compared with the general population cohort by years after cancer diagnosis is shown in Table 3. Although the risk of all types of respiratory disease decreased over the follow up periods, the risks were higher among HNC survivors than the general population cohort. The risks of COPD and aspiration pneumonitis were more than 3 fold higher among HNC survivors than individuals from the general population cohort within two years after cancer diagnosis.
Table 3.
Adverse respiratory outcomes among head and neck cancer survivors (N=1901) and the general population cohort (N=7796) by years after diagnosis
| 0-2 years after cancer diagnosis | 2-5 years after cancer diagnosis | >5 years after cancer diagnosis | ||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| IR per 1000 | HR* | 95% CI | IR per 1000 | HR* | 95% CI | IR per 1000 | HR* | 95% CI | ||||||
| HNC | GP | HNC | GP | HNC | GP | |||||||||
| Overall diseases of the respiratory system | 797.3 | 124.6 | 6.61 | 5.99-7.29 | 137.1 | 64.3 | 2.34 | 2.10-2.61 | 76.6 | 47.0 | 1.88 | 1.66-2.13 | ||
| Respiratory infection | 224.1 | 65.3 | 3.10 | 2.75-3.49 | 61.7 | 35.8 | 1.75 | 1.52-2.01 | 40.6 | 27.6 | 1.63 | 1.40-1.90 | ||
| Chronic obstructive pulmonary diseases and bronchiectasis | 148.3 | 23.3 | 4.97 | 4.17-5.93 | 36.2 | 11.5 | 2.64 | 2.13-3.28 | 24.9 | 9.3 | 2.65 | 2.13-3.29 | ||
| Aspiration pneumonitis | 55.2 | 2.4 | 32.82 | 19.44-55.39 | 7.8 | 1.7 | 4.64 | 2.86-7.54 | 8.4 | 1.4 | 6.21 | 3.98-9.68 | ||
Abbreviations: HNC, head and neck cancer survivor; GP, general population cohort; IR, incidence rate per 1000; HR, hazard ratio; CI, confidence interval.
Adjusted by baseline Charlson Comorbidity Index, race, baseline body mass index and baseline smoking.
We evaluated demographic and clinical characteristics and their potential associations with the risk of adverse respiratory outcomes among HNC survivors who survived for at least 5 years after cancer diagnosis (Table 4). Low BMI at baseline increased the risk of COPD and respiratory infection among HNC survivors. Ever smoking before cancer diagnosis did not increase the risk of aspiration pneumonitis or respiratory infections, but did increase the risk of COPD among HNC survivors (Table 4).Furthermore, women had an increased risk of respiratory infection compared to men. As for clinical characteristics, patients diagnosed with cancers of the oropharynx and hypopharynx had increased risks of respiratory infection compared to oral cavity cancer patients (Supplemental Table 2). Additionally, HNC patients had an increased risk of aspiration pneumonitis when treated with surgery+RT (HR=2.12, 1.11, 4.04), or surgery+RT+CT (HR=4.49; 95%CI=2.17, 9.28).
Table 4.
Associations of selected personal characteristics in relation to occurrence of respiratory disease among head and neck cancer survivors >5 years after diagnosis
| Respiratory infection |
Chronic obstructive pulmonary diseases and bronchiectasis |
Aspiration pneumonitis | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|
| IR per 1000 |
HR * |
95% CI | IR per 1000 |
HR * |
95% CI | IR per 1000 |
HR * |
95% CI | |||
| Age at diagnosis (years) | |||||||||||
| <65 | 39.9 | 1.00 | REF | 23.3 | 1.00 | REF | 7.8 | 1.00 | REF | ||
| ≥65 | 42.5 | 1.18 | 0.91-1.53 | 29.2 | 1.32 | 0.96-1.81 | 10.0 | 1.47 | 0.88-2.48 | ||
| Sex | |||||||||||
| Male | 37.7 | 1.00 | REF | 23.8 | 1.00 | REF | 7.9 | 1.00 | REF | ||
| Female | 49.3 | 1.38 | 1.08-1.77 | 27.9 | 1.18 | 0.86-1.60 | 9.6 | 1.19 | 0.71-1.98 | ||
| Race | |||||||||||
| White | 40.3 | 1.00 | REF | 24.7 | 1.00 | REF | 8.3 | 1.00 | REF | ||
| Other | 53.0 | 1.28 | 0.68-2.41 | 29.8 | 1.07 | 0.47-2.42 | 9.6 | 1.11 | 0.27-4.53 | ||
| Charlson Comorbidity Index | |||||||||||
| 0 | 38.6 | 1.00 | REF | 21.3 | 1.00 | REF | 7.5 | 1.00 | REF | ||
| ≥1 | 46.6 | 1.36 | 1.03-1.79 | 35.9 | 1.59 | 1.15-2.21 | 11.0 | 1.49 | 0.85-2.62 | ||
| BMI at baseline (kg/m2) | |||||||||||
| <18.5 | 93.6 | 2.66 | 1.11-6.37 | 98.9 | 6.31 | 2.47-16.09 | 13.5 | 2.01 | 0.25-15.89 | ||
| ≥18.5 to <25 | 40.2 | 1.00 | REF | 23.7 | 1.00 | REF | 7.3 | 1.00 | REF | ||
| ≥25 to <30 | 40.1 | 0.99 | 0.77-1.28 | 24.1 | 1.02 | 0.74-1.41 | 10.0 | 1.39 | 0.82-2.35 | ||
| ≥30 | 40.1 | 0.97 | 0.69-1.36 | 25.9 | 1.07 | 0.71-1.62 | 6.7 | 0.90 | 0.42-1.94 | ||
| Baseline smoking | |||||||||||
| Non-smoker | 40.5 | 1.00 | REF | 21.6 | 1.00 | REF | 7.8 | 1.00 | REF | ||
| Smoker | 41.0 | 1.08 | 0.72-1.61 | 42.2 | 1.93 | 1.28-2.91 | 11.3 | 1.60 | 0.76-3.36 | ||
Abbreviations: IR, incidence rate per 1000; HR, hazard ratio; CI, confidence interval; REF, reference; BMI, body mass index
Adjustment by age at diagnosis, sex, race, baseline Charlson Comorbidity, baseline BMI, baseline smoking, treatment modality, subsite, and clinical disease stage.
Discussion
In this study, we observed that HNC survivors had increased risks of adverse respiratory outcomes compared to the general population cohort in all of the follow up periods, including 0–2 years, 2–5 years and > 5 years after cancer diagnosis. Using the SEER registry, several studies have investigated mortality due to competing causes among HNC survivors 12-15. Among them, Rose et al. reported that the 5-year cumulative incidences were 51.5% for all-cause mortality, 23.8% for HNC-specific mortality, and 27.6% for competing mortality 12. In addition, the most common causes of non-cancer mortality were cardiovascular disease, COPD, and second primary tumors.
It has been established that smoking is strongly associated with the development of COPD 16. Approximately 30% of HNC survivors continue to smoke even after cancer treatment 17, 18. For cancer survivors, anxiety of recurrence and depression may lead to smoking relapse 19, 20, which in turn may increase the risk of COPD. We identified a significant association of pretreatment smoking status only with the risk of COPD among HNC survivors in this study. There may have been limitations in identifying tobacco smokers with CPT and ICD codes in our study. As for the treatment of COPD, early detection and smoking cessation can prevent disease progression and improve outcome 21. For HNC survivors, we should intervene for both early detection of COPD and smoking cessation programs. Indeed, smoking cessation intervention is effective for HNC survivors, especially in the perioperative period 22.
Dysphagia is one of the most common side effects related to treatment modality among HNC patients 23. Surgery is directly associated with swallowing function and RT induce to the fibrosis of muscle related to swallowing. In this study, compared with HNC patients treated with surgery only, HNC patients treated with RT had increased risks of aspiration pneumonitis. Moreover, the triple treatment modality was the strongest risk factor for aspiration pneumonitis. Francis et al. reported that approximately half of locoregionally advanced HNC patients treated with multimodality therapy had some degree of chronic dysphagia 24. We should consider early swallowing interventions for HNC survivors. Indeed, early intervention during treatment may be effective for preventing aspiration pneumonitis 25.
Malnutrition is often observed among HNC survivors and is associated with dysphagia, altered or loss of taste, and psychological issues 23, 26. Malnutrition leads to immune deficiency and may increase the risk of respiratory infection 27. Moreover, poor oral hygiene due to xerostomia or trismus may increase respiratory infection 28. Therefore, management of oral hygiene should be considered among HNC survivors. In addition, smoking may be associated with immunodeficiency 29. Similarly, smoking cessation should be considered for HNC survivors.
A limitation of the study is that misclassification of late effects may be possible if the ICD was not coded consistently. Although the methodology to assess late effects among head and neck cancer patients and the general population cohort were the same, it is likely that the HNC survivors were more closely monitored in their follow up care for recurrences as well as general health. We would expect that surveillance bias would be minimized especially >5 years after cancer diagnosis. We also did not have data on quality of life, socioeconomic status or lifestyle factors such as alcohol and physical activity. BMI may act as a marker for physical activity, but it is drawn from the driver’s license records, which are self-reported. Although weight may be underestimated and height may be overestimated by individuals, we would not expect the reporting of height and weight to be different in the head and neck cancer patients compared to the general population cohort. Using the EMR to identify smokers likely undercounts smoking, and misclassifies some smokers as non-smokers, although we did detect increased risks of COPD due to smoking. The misclassification of some of the smokers as non-smokers may be non-differential between HNC survivors and the general population cohort, since smoking was assessed for individuals before their cancer diagnosis, leading to bias towards the null. The use of EMR excludes the possibility of recall bias, but if an individual leaves Utah, we would not be able to follow them up. However, the majority of cancer patients were linked and had outcome data in the multiple databases (>98%) and out-migration from the state is fairly low at 2.9% 30. The Utah population is less diverse than the general US population, thus our results are not generalizable to more diverse populations. Some of the risk factors were restricted by small sample sizes of the patients with the respiratory outcomes. The cancer treatment data was restricted to first course treatment from the cancer registry. We were unable to capture additional cancer treatment that the patients may have had due to recurrences. Finally, we did not have data on the chemotherapeutic agents in our study, but in the future we plan to supplement the cohort data with this information.
Some strengths of our study include the population-based design covering the entire Utah population of approximately 2.9 million individuals. To our knowledge, this is one of the first large-scale population-based studies of HNC survivors in the USA, which had incident respiratory disease assessments. We did not rely on patient recall since our study is based on EMR; thus, recall bias is not an issue in our study. Our medical record linkage is very high and the amount of outcome data available would be difficult to obtain in other studies of cancer survivors that rely on questionnaires.
In conclusion, we demonstrated that the risk of respiratory late effects among HNC survivors was much higher than the general population. Moreover, clinical factors including treatment modality, subsite and clinical disease stage were associated with respiratory disease risk more than demographic factors. Multidisciplinary care for smoking cessation, swallowing rehabilitation and emotional side effects is needed to prevent the incidence of respiratory late effects among HNC survivors.
Supplementary Material
Acknowledgement
This work was supported by a grant from the National Cancer Institute at the National Institutes of Health (grant number R03 159357, R21 CA185811, Hashibe, PI; R21 DE027178, Monroe/Hashibe) and the National Center for Research Resources grant, “Sharing Statewide Health Data for Genetic Research” (R01 RR021746, G. Mineau, PI) with additional support from the Utah State Department of Health and the University of Utah. We thank the Pedigree and Population Resource of the Huntsman Cancer Institute, University of Utah (funded in part by the Huntsman Cancer Foundation) for its role in the ongoing collection, maintenance and support of the Utah Population Database (UPDB). We thank the University of Utah Center for Clinical and Translational Science (CCTS) (funded by NIH Clinical and Translational Science Awards), the Pedigree and Population Resource, University of Utah Information Technology Services and Biomedical Informatics Core for establishing the Master Subject Index between the Utah Population Database, the University of Utah Health Sciences Center and Intermountain Healthcare. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.
Footnotes
Conflict of Interest
All authors declare no conflict of interest.
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