Objective
Erosive hand osteoarthritis (OA) is a severe and rapidly progressing subset of hand OA. Its etiology remains largely unknown, which has hindered development of successful treatments. This ...study was undertaken to test the hypothesis that erosive hand OA demonstrates familial clustering in a large statewide population linked to genealogical records, and to determine the association of potential risk factors with erosive hand OA.
Methods
Patients diagnosed as having erosive hand OA were identified by searching 4,741,840 unique medical records from a comprehensive statewide database, the Utah Population Database (UPDB). Affected individuals were mapped to pedigrees to identify high‐risk families with excess clustering of erosive hand OA as defined by a familial standardized incidence ratio (FSIR) of ≥2.0. The magnitude of familial risk of erosive hand OA in related individuals was calculated using Cox regression models. Association of potential erosive hand OA risk factors was analyzed using multivariate conditional logistic regression and logistic regression models.
Results
We identified 703 affected individuals linked to 240 unrelated high‐risk pedigrees with excess clustering of erosive hand OA (FSIR ≥2.0, P < 0.05). The relative risk of developing erosive hand OA was significantly elevated in first‐degree relatives (P < 0.001). There were significant associations between a diagnosis of erosive hand OA and age, sex, diabetes, and obesity (all P < 0.05).
Conclusion
Familial clustering of erosive hand OA observed in a statewide database indicates a potential genetic contribution to the etiology of the disease. Age, sex, diabetes, and obesity are risk factors for erosive hand OA. Identification of causal gene variants in these high‐risk families may provide insight into the genes and pathways that contribute to erosive hand OA onset and progression.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SAZU, SBCE, SBMB, UL, UM, UPUK
Socially disadvantaged groups generally are more likely to reside in areas with less desirable conditions. We examined longitudinal relationships between neighborhood resident characteristics and ...amenities from 1990 to 2010 in an urban area of Utah, U.S. Four temporal patterns of social inequities are described using mixed-effects models: historical inequities; differential selection into amenity-rich tracts; differential investment in amenities; and simultaneous twenty-year change. Results indicate historical differences by neighborhood socioeconomic status, with lower status tracts having fewer green/natural amenities and higher air pollution in 1990 but also greater walkability and more food stores. Differences in amenities by neighborhood socioeconomic status widened over time as aggregate socioeconomic status disproportionately increased in tracts with more green/natural amenities, less air pollution, and lower walkability in 1990, consistent with differential selection. Tract percentage non-Hispanic White did not predict historical differences, but tracts that were less walkable and had fewer healthy food stores in 1990 experienced larger subsequent increases in racial/ethnic diversity. Tracts with higher relative to lower percentage non-Hispanic White in 1990 had larger decreases in air pollution but declining green/natural amenities. This study shows how social inequities in neighborhood amenities change over time, providing evidence of historical socioeconomic differences increasing from differential resident selection.
•Urban and nature-based amenities for four urban counties were assessed over 20 years.•Socioeconomically advantaged areas had more nature-based but fewer urban amenities.•Socioeconomic differences widened as higher status residents moved into amenity-rich areas.•Racial composition was not associated with neighborhood amenities in 1990.•Racial diversity increased in areas that initially had fewer urban amenities.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Importance Endometriosis has been associated with an increased risk of ovarian cancer; however, the associations between endometriosis subtypes and ovarian cancer histotypes have not been ...well-described. Objective To evaluate the associations of endometriosis subtypes with incidence of ovarian cancer, both overall and by histotype. Design, Setting, and Participants Population-based cohort study using data from the Utah Population Database. The cohort was assembled by matching 78 893 women with endometriosis in a 1:5 ratio to women without endometriosis. Exposures Endometriosis cases were identified via electronic health records and categorized as superficial endometriosis, ovarian endometriomas, deep infiltrating endometriosis, or other. Main Outcomes and Measures Estimated adjusted hazard ratios (aHRs), adjusted risk differences (aRDs) per 10 000 women, and 95% CIs for overall ovarian cancer, type I ovarian cancer, and type II ovarian cancer comparing women with each type of endometriosis with women without endometriosis. Models accounted for sociodemographic factors, reproductive history, and past gynecologic operations. Results In this Utah-based cohort, the mean (SD) age at first endometriosis diagnosis was 36 (10) years. There were 597 women with ovarian cancer. Ovarian cancer risk was higher among women with endometriosis compared with women without endometriosis (aHR, 4.20 95% CI, 3.59-4.91; aRD, 9.90 95% CI, 7.22-12.57), and risk of type I ovarian cancer was especially high (aHR, 7.48 95% CI, 5.80-9.65; aRD, 7.53 95% CI, 5.46-9.61). Ovarian cancer risk was highest in women with deep infiltrating endometriosis and/or ovarian endometriomas for all ovarian cancers (aHR, 9.66 95% CI, 7.77-12.00; aRD, 26.71 95% CI, 20.01-33.41), type I ovarian cancer (aHR, 18.96 95% CI, 13.78-26.08; aRD, 19.57 95% CI, 13.80-25.35), and type II ovarian cancer (aHR, 3.72 95% CI, 2.31-5.98; aRD, 2.42 95% CI, −0.01 to 4.85). Conclusions and Relevance Ovarian cancer risk was markedly increased among women with ovarian endometriomas and/or deep infiltrating endometriosis. This population may benefit from counseling regarding ovarian cancer risk and prevention and could be an important population for targeted screening and prevention studies.
Periprosthetic joint infection (PJI) is a devastating complication after total joint arthroplasty, carrying significant economic and personal burden. The goal of this study is to use an established ...database to analyze socioeconomic variables and assess their relationship to PJI. Additionally, we sought to evaluate whether socioeconomic factors, along with other known risk factors of PJI, when controlled for in a statistical model affected the familial risk of PJI.
With approval from our Institutional Review Board we performed a population-based retrospective cohort study on all primary total joint arthroplasty cases of the hip or knee (n = 85,332), within a statewide database, between January 1996 and December 2013. We excluded 9854 patients due to age <18 years, missing data, history of PJI prior to index procedure, and no evidence of 2-year follow-up (excluding those with PJI). Cases that developed PJI following the index procedure (n = 2282) were compared to those that did not (n = 73,196).
After adjusting for covariates, patients with Medicaid as a primary payer were at greater risk for experiencing PJI (relative risk 1.40, 95% confidence interval CI 1.08-1.82, P = .01). There was no difference in risk between the groups associated with education level or median household income (all, P > .05). First-degree relatives of patients who develop PJI (hazard ratio 1.66, 95% CI 1.23-2.24, P = .001) and first-degree and second-degree relatives combined (hazard ratio 1.39, 95% CI 1.09-1.77, P = .007) were at greater risk despite controlling for the above socioeconomic factors.
Our study provides further support that genetic factors may underlie PJI as we did observe significant familial risk even after accounting for socioeconomic factors and payer status. We did not find a correlation between education level or household income and PJI; however, Medicaid payees were at increased risk. Continued study is needed to define a possible heritable disposition to PJI in an effort to optimize treatment and possibly prevent this complication.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
To determine if there is evidence of heritable risk for nonunion using a large, state-wide population database.
Database.
Level 1 Trauma Center.
All Utah residents from 1996 - 2021 that sustained a ...long bone fracture and their family members.
The primary outcome was nonunion and the prevalence of nonunion among the patients' first-, second-, and third-degree relatives. The secondary objective was to identify demographic, injury, and socioeconomic risk factors associated with nonunion.
In total, 150,263 fractures and 6,577 (4.4%) nonunions were identified. This was highly refined to a 1:3 matched cohort of 4,667 nonunions of 13,981 fractures for familial clustering analysis. Cox proportional hazards did not demonstrate excessive risk of nonunion amongst first- (p = 0.863), second- (p = 0.509), and third-degree relatives (p = 0.252). Further analysis of the entire cohort demonstrated male sex (RR = 1.15; p < 0.001), Medicaid enrollment (RR = 2.64; p < 0.001), open fracture (RR = 2.53; p < 0.001), age group 41-60 (RR = 1.43; p < 0.001), a history of obesity (RR = 1.20; p < 0.001) were independent risk factors for nonunion.
Our results demonstrate no evidence of heritable risk for nonunion. Independent risk factors for nonunion were male sex, Medicaid enrollment, open fracture, middle age, and a history of obesity. While it is important to identify modifiable and non-modifiable risk factors, these results continue to support that the risk of nonunion is multifactorial, relating to injury characteristics, operative techniques, and patient specific risk factors.
Level III. See Instructions for Authors for a complete description of levels of evidence.
PURPOSEOur goals were to identify individuals who required surgery for thumb carpometacarpal (CMC) joint osteoarthritis (OA), determine if CMC joint OA clusters in families, define the magnitude of ...familial risk of CMC joint OA, identify risk factors associated with CMC joint OA, and identify rare genetic variants that segregate with familial CMC joint OA. METHODSWe searched the Utah Population Database to identify a cohort of CMC joint OA patients who required surgery. Affected individuals were mapped to pedigrees to identify high-risk families with excess clustering of CMC joint OA. Cox regression models were used to calculate familial risk of CMC joint OA in related individuals. Risk factors were evaluated using logistic regression models. Whole exome sequencing was used to identify rare coding variants associated with familial CMC joint OA. RESULTSWe identified 550 pedigrees with excess clustering of severe CMC joint OA. The relative risk of CMC joint OA requiring surgical treatment was elevated significantly in first- and third-degree relatives of affected individuals, and significant associations with advanced age, female sex, obesity, and tobacco use were observed. We discovered candidate genes that dominantly segregate with severe CMC joint OA in 4 independent families, including a rare variant in Chondroitin Sulfate Synthase 3 (CHSY3). CONCLUSIONSFamilial clustering of severe CMC joint OA was observed in a statewide population. Our data indicate that genetic and environmental factors contribute to the disease process, further highlighting the multifactorial nature of the disease. Genomic analyses suggest distinct biological processes are involved in CMC joint OA pathogenesis. CLINICAL RELEVANCEAwareness of associated comorbidities may guide the diagnosis of CMC joint OA in at-risk populations and help identify individuals who may not do well with nonoperative treatment. Further pursuit of the genes associated with severe CMC joint OA may lead to assays for detection of early stages of disease and have therapeutic potential.
Introduction
Acute extremity compartment syndrome (“CS”) is an under-researched, highly morbid condition affecting trauma populations. The purpose of this study was to analyze incidence rates and ...risk factors for extremity compartment syndrome using a high-quality population database. Additionally, we evaluated heritable risk for CS using available genealogic data. We hypothesized that diagnosis of extremity compartment syndrome would demonstrate heritability.
Materials and methods
Adult patients with fractures of the tibia, femur, and upper extremity were retrospectively identified by ICD-9, ICD-10, and CPT codes from 1996 to 2020 in a statewide hospital database. Exposed and unexposed cohorts were created based on a diagnosis of CS. Available demographic data were analyzed to determine risk factors for compartment syndrome using logistic regression. Mortality risk at the final follow-up was evaluated using Cox proportional hazard modeling. Patients with a diagnosis of CS were matched with those without a diagnosis for heritability analysis.
Results
Of 158,624 fractures, 931 patients were diagnosed with CS. Incidence of CS was 0.59% (tibia 0.83%, femur 0.31%, upper extremity 0.27%). Male sex (78.1% vs. 46.4%;
p
< 0.001; RR = 3.24), younger age at fracture (38.8 vs. 48.0 years;
p
< 0.001; RR = 0.74), Medicaid enrollment (13.2% vs. 9.3%;
p
< 0.001; RR = 1.58), and smoking (41.1% vs. 31.1%;
p
< 0.001; RR 1.67) were significant risk factors for CS. CS was associated with mortality (RR 1.61,
p
< 0.001) at mean follow-up 8.9 years in the CS cohort. No significant heritable risk was found for diagnosis of CS.
Conclusions
Without isolating high-risk fractures, rates of CS are lower than previously reported in the literature. Male sex, younger age, smoking, and Medicaid enrollment were independent risk factors for CS. CS increased mortality risk at long-term follow-up. No heritable risk was found for CS.
Level of evidence
III.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
Ageing may be due to mutation accumulation across the lifespan, leading to tissue dysfunction, disease, and death. We tested whether germline autosomal mutation rates in young adults predict their ...remaining survival, and, for women, their reproductive lifespans. Age-adjusted mutation rates (AAMRs) in 61 women and 61 men from the Utah CEPH (Centre d'Etude du Polymorphisme Humain) families were determined. Age at death, cause of death, all-site cancer incidence, and reproductive histories were provided by the Utah Population Database, Utah Cancer Registry, and Utah Genetic Reference Project. Higher AAMRs were significantly associated with higher all-cause mortality in both sexes combined. Subjects in the top quartile of AAMRs experienced more than twice the mortality of bottom quartile subjects (hazard ratio HR, 2.07; 95% confidence interval CI, 1.21-3.56; p = 0.008; median survival difference = 4.7 years). Fertility analyses were restricted to women whose age at last birth (ALB) was ≥ 30 years, the age when fertility begins to decline. Women with higher AAMRs had significantly fewer live births and a younger ALB. Adult germline mutation accumulation rates are established in adolescence, and later menarche in women is associated with delayed mutation accumulation. We conclude that germline mutation rates in healthy young adults may provide a measure of both reproductive and systemic ageing. Puberty may induce the establishment of adult mutation accumulation rates, just when DNA repair systems begin their lifelong decline.
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IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
We previously showed that the
variant c.5096G>A p.Arg1699Gln (R1699Q) was associated with an intermediate risk of breast cancer (BC) and ovarian cancer (OC). This study aimed to assess these cancer ...risks for R1699Q carriers in a larger cohort, including follow-up of previously studied families, to further define cancer risks and to propose adjusted clinical management of female
*R1699Q carriers.
Data were collected from 129
*R1699Q families ascertained internationally by ENIGMA (Evidence-based Network for the Interpretation of Germline Mutant Alleles) consortium members. A modified segregation analysis was used to calculate BC and OC risks. Relative risks were calculated under both monogenic model and major gene plus polygenic model assumptions.
In this cohort the cumulative risk of BC and OC by age 70 years was 20% and 6%, respectively. The relative risk for developing cancer was higher when using a model that included the effects of both the R1699Q variant and a residual polygenic component compared with monogenic model (for BC 3.67 vs 2.83, and for OC 6.41 vs 5.83).
Our results confirm that
*R1699Q confers an intermediate risk for BC and OC. Breast surveillance for female carriers based on mammogram annually from age 40 is advised. Bilateral salpingo-oophorectomy should be considered based on family history.
e18817
Background: Immunotherapy harnesses cancer patients’ immune systems to eradicate cancer cells, and has become the standard of care as first line or combination therapy in advanced lung cancer. ...While immunotherapy is more tolerable than other treatments such as chemotherapy, a minority of patients experience toxicities requiring clinical intervention. The aim of this study is to examine the risk of all-cause inpatient and emergency department visits among lung cancer patients diagnosed with cancer receiving immunotherapies as first line treatments using a linked population dataset. Methods: We analyzed administrative data from N = 3,268 lung cancer patients diagnosed between 2013 and 2018 from the Immunotherapy, Palliative and End-of-life Treatment Utilization and Spousal Outcomes (ImmPETUS) cohort, a linked population-based cohort of melanoma, lung, breast, colorectal and bladder cancer patients and their spouses in Utah. Analyses were conducted with multivariable logistic regression models in R and adjusted for sex, age, age at diagnosis, cancer stage, race, ethnicity, marital status, neighborhood education and household income, insurance type, rurality and comorbidity. Results: Among patients diagnosed with lung and bronchus cancers (53.1% male, 46.9% female), 9.5% received immunotherapy as a first line treatment and 57.3% had distant stages at diagnosis. Adjusting for race, ethnicity, neighborhood education and income, and rurality, lung cancer patients who received immunotherapies as a first course of treatment had greater odds of all-cause emergency department encounters (aOR = 1.94, 95% CI = 1.49-2.53, p < 0.001) compared to patients receiving other first line treatments. Non-Medicaid patients and patients with greater comorbidities were less likely to have all-cause emergency department encounters (aOR = 0.66, 95% CI = 0.53-0.82, p < 0.001; 0.92, 95% CI = 0.89-0.96, p < 0.001) and all-cause inpatient visits (aOR = 0.60, 95% CI = 0.46-0.77, p < 0.001; aOR = 0.89, 95% CI = 0.85-0.93, p < 0.001) compared with Medicaid patients and patients with no comorbidities. Nonmarried patients (aOR = 0.71, 95% CI 0.59-0.86, p < 0.001) were less likely to have all-cause inpatient visits compared with those who were married/partnered. Conclusions: Our findings support that patients receiving immunotherapies as first line treatment have increased risk of all-cause emergency department encounters. This analysis of real-world data enabled the examination of downstream healthcare utilization outcomes of immunotherapy cancer patients within Utah, and provides insight into groups at risk for adverse events. Future directions include examining the clinical and social pathways of these disparities, such as immune-related adverse events, access to supportive care, and supports for patient and family decision making.
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