Fine-Gray Subdistribution Hazard Model Research Articles

Home, but Not Homebound: A Prospective Analysis of Persons Living With Dementia.

Homebound persons living with dementia may have increased difficulty accessing needed care in the community. This study identifies factors associated with becoming homebound among a national sample of Medicare beneficiaries with newly identified dementia. Prospective cohort analysis. We used the National Health and Aging Trends Study (NHATS) 2011-2018 to identify community-dwelling older adults at the time of a new dementia diagnosis (n= 939). Dementia status was determined based on cognitive testing and self and proxy reporting. We compared characteristics of homebound (ie, those who never or rarely left home) and non-homebound participants at the time of dementia identification. Among non-homebound participants, we used a Fine-Gray subdistribution hazard model to identify factors associated with becoming homebound over follow-up (median follow-up 4years), accounting for competing risks of death and moving to a nursing home. 20% of individuals with newly identified dementia were homebound and this group was more functionally impaired, medically complex, and socioeconomically disadvantaged as compared to the non-homebound. Over time, depression [subhazard ratio (SHR) 2.19, 95% CI 1.36, 3.54], living in an assisted living facility (SHR 2.60, 95% CI 1.35, 4.97), and Hispanic ethnicity (SHR 1.91, 95% CI 1.05, 3.47) were associated with becoming homebound. Most adults are not homebound at the time of dementia diagnosis. Identifying and addressing modifiable factors like depression may slow progression to homebound status and enable persons living with dementia to access needed care in the community. In order to accommodate diverse individual and family preferences for long-term care, robust systems of home-based clinical and long-term care are necessary for those who do become homebound.

Benzodiazepines in Patients with Heart Failure and Reduced Ejection Fraction.

In patients with heart failure (HF), anxiety or insomnia is prevalent and associated with poor clinical outcomes. Benzodiazepines (BZDs) are one of the most commonly prescribed medications for anxiety or insomnia in Taiwan. Evidence regarding the effects of BZDs on patients with heart failure and reduced ejection fraction (HFrEF) is inconclusive. To evaluate whether BZDs can mitigate the adverse effects of anxiety or insomnia on the prognosis of patients with HFrEF. Patients with HFrEF were identified from the Chang Gung Research Database between January 1, 2007 and December 31, 2018. Those who received BZD prescriptions were defined as the BZD group; patients in the BZD group were then paired with those who had never been prescribed BZDs after matching for age, sex, and baseline left ventricular ejection fraction, defined as the no-BZD group. Propensity score matching was used to balance baseline characteristics. Cox proportional hazards model and the Fine-Gray subdistribution hazard model were used to examine the association between BZD prescription and the risks of adverse cardiovascular outcomes. After propensity score matching, there were 1,941 patients in both BZD and no-BZD groups. The composite of cardiovascular (CV) death or HF hospitalization (HFH) occurred in 64.4% and 54.4% of the patients in the BZD and no-BZD groups, respectively [hazard ratio (HR): 1.44; 95% confidence interval (CI): 1.32-1.56], which was mainly driven by HFH (HR: 1.52; 95% CI: 1.39-1.67). In the patients with HFrEF, those who received BZD were at a higher overall risk of CV death and HFH.

Background Parenchymal Enhancement at Postoperative Surveillance Breast MRI: Association with Future Second Breast Cancer Risk.

Background Background parenchymal enhancement (BPE) is a known risk factor for breast cancer. However, studies on the association between BPE and second breast cancer risk are still lacking. Purpose To investigate whether BPE at surveillance breast MRI is associated with subsequent second breast cancer risk in women with a personal history of breast cancer. Materials and Methods A retrospective search of the imaging database of an academic medical center identified consecutive surveillance breast MRI examinations performed between January 2008 and December 2017 in women who underwent surgery for primary breast cancer and had no prior diagnosis of second breast cancer. BPE at surveillance breast MRI was qualitatively assessed using a four-category classification of minimal, mild, moderate, or marked. Future second breast cancer was defined as ipsilateral breast tumor recurrence or contralateral breast cancer diagnosed at least 1 year after each surveillance breast MRI examination. Factors associated with future second breast cancer risk were evaluated using the multivariable Fine-Gray subdistribution hazard model. Results Among the 2668 women (mean age at baseline surveillance breast MRI, 49 years ± 8 [SD]), 109 developed a second breast cancer (49 ipsilateral, 58 contralateral, and two ipsilateral and contralateral) at a median follow-up of 5.8 years. Mild, moderate, or marked BPE at surveillance breast MRI (hazard ratio [HR], 2.1 [95% CI: 1.4, 3.1]; P < .001), young age (<45 years) at initial breast cancer diagnosis (HR, 3.4 [95% CI: 1.7, 6.4]; P < .001), positive results from a BRCA1/2 genetic test (HR, 6.5 [95% CI: 3.5, 12.0]; P < .001), and negative hormone receptor expression in the initial breast cancer (HR, 1.6 [95% CI: 1.1, 2.6]; P = .02) were independently associated with an increased risk of future second breast cancer. Conclusion Background parenchymal enhancement at surveillance breast MRI was associated with future second breast cancer risk in women with a personal history of breast cancer. © RSNA, 2022 Online supplemental material is available for this article. See also the editorial by Niell in this issue.

Assessment of Lung Cancer Risk Among Smokers for Whom Annual Screening Is Not Recommended

The US Preventive Services Task Force does not recommend annual lung cancer screening with low-dose computed tomography (LDCT) for adults aged 50 to 80 years who are former smokers with 20 or more pack-years of smoking who quit 15 or more years ago or current smokers with less than 20 pack-years of smoking. To determine the risk of lung cancer in older smokers for whom LDCT screening is not recommended. This cohort study used the Cardiovascular Health Study (CHS) data sets obtained from the National Heart, Lung and Blood Institute, which also sponsored the study. The CHS enrolled 5888 community-dwelling individuals aged 65 years and older in the US from June 1989 to June 1993 and collected extensive baseline data on smoking history. The current analysis was restricted to 4279 individuals free of cancer who had baseline data on pack-year smoking history and duration of smoking cessation. The current analysis was conducted from January 7, 2022, to May 25, 2022. Current and prior tobacco use. Incident lung cancer during a median (IQR) of 13.3 (7.9-18.8) years of follow-up (range, 0 to 22.6) through December 31, 2011. A Fine-Gray subdistribution hazard model was used to estimate incidence of lung cancer in the presence of competing risk of death. Cox cause-specific hazard regression models were used to estimate hazard ratios (HRs) and 95% CIs for incident lung cancer. There were 4279 CHS participants (mean [SD] age, 72.8 [5.6] years; 2450 [57.3%] women; 663 [15.5%] African American, 3585 [83.8%] White, and 31 [0.7%] of other race or ethnicity) included in the current analysis. Among the 861 nonheavy smokers (<20 pack-years), the median (IQR) pack-year smoking history was 7.6 (3.3-13.5) pack-years for the 615 former smokers with 15 or more years of smoking cessation, 10.0 (5.3-14.9) pack-years for the 146 former smokers with less than 15 years of smoking cessation, and 11.4 (7.3-14.4) pack-years for the 100 current smokers. Among the 1445 heavy smokers (20 or more pack-years), the median (IQR) pack-year smoking history was 34.8 (26.3-48.0) pack-years for the 516 former smokers with 15 or more years of smoking cessation, 48.0 (35.0-70.0) pack-years for the 497 former smokers with less than 15 years of smoking cessation, and 48.8 (31.6-57.0) pack-years for the 432 current smokers. Incident lung cancer occurred in 10 of 1973 never smokers (0.5%), 5 of 100 current smokers with less than 20 pack-years of smoking (5.0%), and 26 of 516 former smokers with 20 or more pack-years of smoking with 15 or more years of smoking cessation (5.0%). Compared with never smokers, cause-specific HRs for incident lung cancer in the 2 groups for whom LDCT is not recommended were 10.54 (95% CI, 3.60-30.83) for the current nonheavy smokers and 11.19 (95% CI, 5.40-23.21) for the former smokers with 15 or more years of smoking cessation; age, sex, and race-adjusted HRs were 10.06 (95% CI, 3.41-29.70) for the current nonheavy smokers and 10.22 (4.86-21.50) for the former smokers with 15 or more years of smoking cessation compared with never smokers. The findings of this cohort study suggest that there is a high risk of lung cancer among smokers for whom LDCT screening is not recommended, suggesting that prediction models are needed to identify high-risk subsets of these smokers for screening.

The association of agent orange (AO) exposure with monoclonal gammopathy of undetermined significance (MGUS) to multiple myeloma (MM) progression: A population-based study.

8050 Background: With limited evidence from a single center study [n=211 (11 with AO exposure)] reporting AO exposure as a risk factor for transformation, whether or not AO exposure increases the rate of transformation from MGUS to MM is unclear. Thus, we aimed to conduct a nation-wide study to determine the association between AO exposure and the risk of MGUS to MM progression. Methods: A retrospective, matched cohort study using data from the U.S. Veterans Health Administration system was conducted. Based on a power calculation, a random sample of MGUS patients with AO exposure was selected and 1:1 matched to those with MGUS without AO exposure (matching factors: age at MGUS diagnosis, race, body mass index categories). Data abstraction confirmed MGUS and MM diagnoses. In addition, information on date of diagnosis, MGUS subtype, and monoclonal protein (M-protein) values was performed. Patients were considered to have MGUS if they had M-protein detected on serum protein electrophoresis (SPEP) with immunofixation confirmation. The association of AO exposure with progression from MGUS to MM was examined using a multivariable Fine-Gray subdistribution hazard model with death as the competing event. The covariates included M-protein at MGUS diagnosis (&gt;1.5, ≤1.5 g/dL [reference]), MGUS subtype (Immunoglobulin A, light chain, and Immunoglobulin G [reference]), and Charlson comorbidity score at MGUS diagnosis. A sensitivity analysis was conducted using inverse probability treatment weighted survival analysis to evaluate the robustness of the conclusion. Results: After excluding individuals with no confirmed MGUS or M MGUS subtype, a total of 563 MGUS patients with AO exposure and 563 matched controls were included. No statistically significant difference was observed in the progression of MGUS to MM between the AO exposed group and control group (adjusted hazard ratio (aHR) 0.78, 95% confidence interval (CI) 0.53 to 1.17). The sensitivity analysis demonstrated consistent results. Conclusions: Our carefully designed study does not show an association between AO exposure and progression of MGUS to MM in a national cohort of Veterans. [Table: see text]

Comorbid Hypertension Reduces the Risk of Ventricular Arrhythmia in Chronic Heart Failure Patients with Implantable Cardioverter-Defibrillators.

Aims: Low blood pressure (BP) has been shown to be associated with increased mortality in patients with chronic heart failure. This study was designed to evaluate the relationships between diagnosed hypertension and the risk of ventricular arrhythmia (VA) and all-cause death in chronic heart failure (CHF) patients with implantable cardioverter-defibrillators (ICD), including those with preserved left ventricular ejection fraction (HFpEF) and indication for ICD secondary prevention. We hypothesized that a stable hypertension status, along with an increasing BP level, is associated with a reduction in the risk of VA in this population, thereby limiting ICD efficacy. Methods: We retrospectively enrolled 964 CHF patients, with hypertension diagnosis and hospitalized BP measurements obtained before ICD implantation. The primary outcome measure was defined as the composite of SCD, appropriate ICD therapy, and sustained VT. The secondary endpoint was time to death or heart transplantation (HTx). We performed multivariable Cox proportional hazard regression and entropy balancing to calculate weights to control for baseline imbalances with or without hypertension. The Fine–Gray subdistribution hazard model was used to confirm the results. The effect of random BP measurements on the primary outcome was illustrated in the Cox model with inverse probability weighting. Results: The 964 patients had a mean (SD) age of 58.9 (13.1) years; 762 (79.0%) were men. During the interrogation follow-up [median 2.81 years (interquartile range: 1.32–5.27 years)], 380 patients (39.4%) reached the primary outcome. A total of 244 (45.2%) VA events in non-hypertension patients and 136 (32.1%) in hypertension patients were observed. A total of 202 (21.0%) patients died, and 31 (3.2%) patients underwent heart transplantation (incidence 5.89 per 100 person-years; 95% CI: 5.16–6.70 per 100 person-years) during a median survival follow-up of 4.5 (IQR 2.8–6.8) years. A lower cumulative incidence of VA events was observed in hypertension patients in the initial unadjusted Kaplan–Meier time-to-event analysis [hazard ratio (HR): 0.65, 95% confidence interval (CI): 0.53–0.80]. The protective effect was robust after entropy balancing (HR: 0.71, 95% CI: 0.56–0.89) and counting death as a competing risk (HR: 0.71, 95% CI: 0.51–1.00). Hypertension diagnosis did not associate with all-cause mortality in this population. Random systolic blood pressure was negatively associated with VA outcomes (p = 0.065). Conclusions: In hospitalized chronic heart failure patients with implantable cardioverter-defibrillators, the hypertension status and higher systolic blood pressure measurements are independently associated with a lower risk of combined endpoints of ventricular arrhythmia and sudden cardiac death but not with all-cause mortality. Randomized controlled trials are needed to confirm the protective effect of hypertension on ventricular arrhythmia in chronic heart failure patients.

Risks and Risk Factors for Contralateral Amputation in Patients who have Undergone Amputation for Chronic Limb Threatening Ischaemia

The aim of this study was to determine the cumulative incidence of, and the risk factors associated with, contralateral amputation in patients with chronic limb threatening ischaemia (CLTI). This was a retrospective cohort study of patients with incident unilateral transmetatarsal (TM), transtibial (TT), or transfemoral (TF) amputation secondary to CLTI, identified from the National Veterans Affairs Surgical Quality Improvement Program database (2004 - 2014). Thirteen potential pre-operative risk factors for contralateral amputation were considered. A competing risk analysis to estimate the cumulative incidence of contralateral amputation was performed using a Fine-Gray subdistribution hazard model. The effect of risk factors on contralateral amputation was estimated by computing subdistribution hazard ratios (sub-HR) with 95% confidence intervals (CI). From the database, 7 360 patients met the inclusion criteria. The contralateral amputation risk was 7.7% and was greatest in those who underwent a TF amputation (9.7%), followed by TT (7.4%) and TM amputation (6.6%) (p < .001). Among the 588 contralateral amputations, 50% were at the TF level, 34% at the TT level, and 16% at the TM level. The adjusted risk of contralateral amputation was greater in those who underwent an incident TF amputation or were Black or Hispanic. The factor that contributed to risk of contralateral amputation to the greatest extent was dialysis (sub-HR, 2.3; 95% CI 1.7 - 3.0; p < .001) while those who were obese (compared with underweight) were at lowest risk (0.67; 95% CI 0.46 - 0.97; p= .030). The one year risk of contralateral amputation in patients with CLTI is related to incident amputation level, medical comorbidities, correlates with race/ethnicity, and body mass index at the time of the incident amputation. The identified risk factors are largely not modifiable; however, they can be used to help identify populations at elevated risk.

No Prognostic Impact of Staging Brain MRI in Patients with Stage IA Non-Small Cell Lung Cancer.

Background Although various guidelines discourage performing brain MRI for staging purposes in asymptomatic patients with clinical stage IA non-small cell lung cancer (NSCLC), evidence regarding their postoperative survival is lacking. Purpose To investigate the survival benefit of performing brain MRI in asymptomatic patients with early-stage NSCLC. Materials and Methods Patients who underwent curative resection between February 2009 and March 2016 for clinical TNM stage T1N0M0 NSCLC were retrospectively included. Patient survival and development of brain metastasis during postoperative surveillance were documented. The cumulative survival rate and incidence of brain metastasis were compared between patients who underwent surgery with or without staging brain MRI by using Cox regression and a Fine-Gray subdistribution hazard model, respectively, for multivariable adjustment. Propensity score matching and inverse probability of treatment weighting were applied for confounder adjustment. Results A total of 628 patients (mean age, 64 years ± 10 [SD]; 319 men) were included, of whom 53% (331 of 628) underwent staging brain MRI. In the multivariable analyses, brain MRI did not show prognostic benefits for brain metastasis-free survival (hazard ratio [HR], 1.06; 95% CI: 0.69, 1.63; P = .79), time to brain metastasis (HR, 1.60; 95% CI: 0.70, 3.94; P = .29), and overall survival (HR, 0.86; 95% CI, 0.54, 1.37; P = .54). Consistent results were obtained after propensity score matching (brain metastasis-free survival [HR, 0.97; 95% CI: 0.60, 1.57; P = .91], time to brain metastasis [HR, 1.29; 95% CI: 0.50, 3.33; P = .60], and overall survival [HR, 0.89; 95% CI: 0.53, 1.51; P = .67]) and inverse probability of treatment weighting. Conclusion No difference was observed between asymptomatic patients with clinical stage IA non-small cell lung cancer who underwent staging brain MRI and those who did not in terms of brain metastasis-free survival, time to brain metastasis, and overall survival. © RSNA, 2022 Online supplemental material is available for this article. See also the editorial by Bizzi and Pascuzzo in this issue.

Handgrip strength asymmetry is associated with the risk of neurodegenerative disorders among Chinese older adults.

BackgroundNeurodegenerative disorders, as the irreversible condition, have a long, silent preclinical period. Recognition of early physical signs of neurodegenerative disorders had important practical implications for identifying at‐risk population. The aim of this study was to investigate whether handgrip strength (HGS) asymmetry was associated with the incidence of neurodegenerative disorders among Chinese older adults.MethodsThis study used the data of participants aged 60 years and over from three waves (2011–2015) of China Health and Retirement Longitudinal Study. HGS asymmetry was measured with HGS ratio (maximal non‐dominant HGS/maximal dominant HGS), with the value less than 0.9 or more than 1.1 considered as HGS asymmetry. Physician‐diagnosed neurodegenerative disorders were identified by self‐reported or proxy‐reported information. Competing risk analysis was conducted to examine the association between HGS asymmetry and incident neurodegenerative disorders, with mortality treated as the competing event.ResultsA total of 4925 participants were included in the analysis [mean (SD) age: 68.1(6.68); female: 49.7%]. Eight hundred and eighty‐eight (18.0%) participants had low HGS and 2227 (45.2%) had HGS asymmetry. During the 4 years of follow‐up, there were 156 cases of neurodegenerative disorders and 422 cases of mortality. The incidence of neurodegenerative disorders was 8.7 per 1000 person‐years [95% confidence interval (CI): 7.4–10.2], and the incidence of mortality was 23.5 per 1000 person‐years (95% CI: 21.4–25.9). Both the cause‐specific model and the Fine–Gray subdistribution hazard model showed that participants with HGS asymmetry had increased hazard of neurodegenerative disorders [hazard ratio (HR) = 1.66, P = 0.002, 95% CI: 1.202–2.297; subdistribution hazard ratio (SHR) = 1.65, P = 0.002, 95% CI: 1.202–2.285]. Low HGS, but not HGS asymmetry, was related to the higher hazard of mortality (HR = 1.61, P < 0.001, 95% CI: 1.297–1.995; SHR = 1.58, P < 0.001, 95% CI: 1.286–1.951).ConclusionsHandgrip strength asymmetry was associated with the future risk of neurodegenerative disorders among Chinese older adults. Public healthcare providers could consider examining HGS asymmetry along with the maximal HGS as a way to identify those at elevated risk of neurodegenerative disorders.

Estimation of the Absolute Risk of Cardiovascular Disease and Other Events: Issues With the Use of Multiple Fine-Gray Subdistribution Hazard Models.

The Fine-Gray subdistribution hazard model is frequently used in the cardiovascular literature to estimate subject-specific probabilities of the occurrence of an event of interest over time in the presence of competing risks. A little-known limitation of this approach is that, for some subjects and for some time points, the sum of the subject-specific probabilities for the different event types (eg, cardiovascular and noncardiovascular death) can exceed one. We used data on 8238 patients hospitalized with congestive heart failure in Ontario, Canada. We fit 2 Fine-Gray subdistribution hazards models, one for cardiovascular death and one for noncardiovascular death and estimated the probability of death due to each cause within 5 years of hospital admission. We also fit 2 cause-specific hazard models for the 2 event types and combined the estimated cause-specific hazard functions to obtain subject-specific estimates of the probabilities of each of the 2 event types occurring within 5 years. When adding the probabilities of 5-year cardiovascular death and 5-year noncardiovascular death obtained from the Fine-Gray subdistribution hazard models, 8.6% of subjects had an estimated probability of 5-year all-cause mortality that exceeded 1 (100%). This problem was avoided by fitting 2 cause-specific hazard models, one for each outcome type, and combining the estimated cause-specific hazard functions to obtain subject-specific estimates of the risk of cardiovascular and noncardiovascular death. The Fine-Gray subdistribution hazard model may be problematic to use for a comprehensive assessment of absolute risks of multiple outcomes, while the combination of 2 cause-specific hazard models shows better statistical behaviour. Cause-specific modeling should not be discarded in competing risk situations.

The Influence of Palliative Care in Hospital Length of Stay and the Timing of Consultation.

Inpatient palliative care may reduce length-of-stay, costs, mortality, and prevent readmissions. Timing of consultation may influence outcomes. The aim of this study was to explore the timing of consultation and its influences patient outcomes. This retrospective study of hospital consultations between July 1, 2019 and December 31, 2019 compared patients seen within 72 hours of admission with those seen after 72 hours. Outcomes length of stay and mortality. Chi-square analyses for categorical variables and independent t-tests for continuous normally distributed variables were done. For nonparametrically distributed outcome variables, Wilcoxon rank sum test was used. For mortality, a time-to-event analysis was used. 30-day readmissions were assessed using the Fine-Gray sub-distribution hazard model. Multiple regression models were used, controlling for other variables. 696 patients were seen, 424 within 72 hours of admission. The average age was 73 and 50.6% were female. Consultation within 72 hours was not associated with a shorter stay for cancer but was for patients with non-cancer illnesses. Inpatient mortality and 30-days mortality were reduced but there was a higher 30-day readmission rate. Palliative consultations within 72 hours of admission was associated with lower hospital stays and inpatient mortality but increased the risk of readmission. Benefits were largely observed in patients followed in continuity. Early inpatient palliative care consultation was associated with reduced hospital mortality, 30-day mortality and length of stay particularly if patients were seen by palliative care prior to hospitalization.

Graphical calibration curves and the integrated calibration index (ICI) for competing risk models

BackgroundAssessing calibration—the agreement between estimated risk and observed proportions—is an important component of deriving and validating clinical prediction models. Methods for assessing the calibration of prognostic models for use with competing risk data have received little attention.MethodsWe propose a method for graphically assessing the calibration of competing risk regression models. Our proposed method can be used to assess the calibration of any model for estimating incidence in the presence of competing risk (e.g., a Fine-Gray subdistribution hazard model; a combination of cause-specific hazard functions; or a random survival forest). Our method is based on using the Fine-Gray subdistribution hazard model to regress the cumulative incidence function of the cause-specific outcome of interest on the predicted outcome risk of the model whose calibration we want to assess. We provide modifications of the integrated calibration index (ICI), of E50 and of E90, which are numerical calibration metrics, for use with competing risk data. We conducted a series of Monte Carlo simulations to evaluate the performance of these calibration measures when the underlying model has been correctly specified and when the model was mis-specified and when the incidence of the cause-specific outcome differed between the derivation and validation samples. We illustrated the usefulness of calibration curves and the numerical calibration metrics by comparing the calibration of a Fine-Gray subdistribution hazards regression model with that of random survival forests for predicting cardiovascular mortality in patients hospitalized with heart failure.ResultsThe simulations indicated that the method for constructing graphical calibration curves and the associated calibration metrics performed as desired. We also demonstrated that the numerical calibration metrics can be used as optimization criteria when tuning machine learning methods for competing risk outcomes.ConclusionsThe calibration curves and numeric calibration metrics permit a comprehensive comparison of the calibration of different competing risk models.

Analysis of Survival Data with Competing Risks in ADRD (Alzheimer's Disease and Related Dementias) Research

Abstract Competing risk is an event that precludes the occurrence of the primary event of interest. For example, when studying risk factors associated with dementia, death before the onset of dementia serve as a competing event. A subject who dies is no longer at risk of dementia. This issue play more important role in ADRD research given the elderly population. Conventional methods for survival analysis assume independent censoring and ignore the competing events. However, there are some challenge issues using those conventional methods in the presence of competing risks. First, no one-to-one link between hazard function and cumulative incidence function (CIF), and Kaplan-Meier approach overestimates the cumulative incidence of the event of interest. Second, the effect of covariates on hazard rate cannot be directly linked to the effect of cumulative incidence (the risk). We will discuss two types of analyses in the presence of competing risk: Cause-specific hazard model and Fine-Gray subdistribution hazard model. Cause-specific hazard model directly quantify the cause-specific hazard among subjects who are at risk of developing the event of interest, while Fine-Gray subdistribution hazard model directly model the effects of covariates on the cumulative incidence function. The type of research questions (Association vs. Prediction) may guide the choice of different statistical approaches. We will illustrate those two competing risk analyses using the large national dataset from National Alzheimer’s Coordinating Center (NACC). We will analyze the association between baseline diabetes status and the incidence of dementia, in which death before the onset of dementia is a competing event.

Association of Physical Activity Level With Risk of Dementia in a Nationwide Cohort in Korea

Current guidelines recommend 500 to 999 metabolic equivalent (MET)-minutes per week (MET-min/wk) of regular physical activity. However, evidence regarding the association between light-intensity physical activity (LPA) and dementia in older adults is inconsistent. To assess the association between physical activity and new-onset dementia, focusing on the dose-response association between physical activity and dementia and the association of LPA with the incidence of dementia. For this nationwide retrospective cohort study, we analyzed 62 286 participants aged 65 years or older without preexisting dementia who had available health checkup data from the Korean National Health Insurance Service database from January 2009 to December 2012. Participants were followed up until December 31, 2013, and data analysis was performed from July 2020 to January 2021. Physical activity level was assessed using a standardized, self-reported questionnaire at baseline. Physical activity-related energy expenditure (in MET-min/wk) was calculated by summing the product of frequency, intensity, and duration. Incidence of dementia. Incidence rates were calculated by dividing the number of events by the person-time at risk (presented as the incidence per 1000 person-years). Hazard ratios (HRs) and 95% CIs for dementia were analyzed according to physical activity level. Competing risk regression was performed by using the Fine-Gray subdistribution hazard model, with mortality as the competing risk for dementia events. Multivariable regression models were constructed with adjustment for various patient characteristics. Incident dementia occurring 2 years after enrollment was assessed, and separate analyses included all follow-up periods. Restricted cubic spline curves were used to examine the association of continuous values of physical activity with dementia. Among 62 286 participants, 60.4% were women, and the mean (SD) age was 73.2 (5.3) years. During a median follow-up of 42 months, 3757 participants (6.0%) developed dementia, and the overall incidence was 21.6 per 1000 person-years. Compared with inactive individuals (0 MET-min/wk), insufficiently active (1-499 MET-min/wk; mean, 284 MET-min/wk), active (500-999 MET-min/wk; mean, 675 MET-min/wk), and highly active participants (≥1000 MET-min/wk; mean, 1627 MET-min/wk) showed 10% (adjusted hazard ratio [HR], 0.90; 95% CI, 0.81-0.99), 20% (adjusted HR, 0.80; 95% CI, 0.71-0.92), and 28% (adjusted HR, 0.72; 95% CI, 0.60-0.83) reduced dementia risk, respectively. Thus, a progressive decrease in the adjusted HR of dementia was associated with increasing physical activity level, and a restricted cubic spline curve showed that this association started with a low amount of total physical activity. This association was consistent regardless of age, sex, and other comorbidities or after censoring for stroke. Compared with total sedentary behavior, even a low amount of LPA (1-299 MET-min/wk; mean, 189 MET-min/wk) was associated with reduced dementia risk (adjusted HR, 0.86; 95% CI, 0.74-0.99). In older adults, an increased physical activity level, including a low amount of LPA, was associated with a reduced risk of dementia. Promotion of LPA might reduce the risk of dementia in older adults.

A pre-operative prognostic model predicting all cause and cause specific mortality for women presenting with invasive breast cancer

PurposeThe aim of this study is to develop a pre-operative prognostic model based on known pre-operative factors. MethodsA database of ultrasound (US) lesions undergoing biopsy documented US lesion size, stiffness, and patient source prospectively. Women with invasive cancer presenting between 2010 and 2015 were the study group. Breast and axillary core results and ER, PR and HER receptor status were collected prospectively. Assessment of US skin thickening, US distal enhancement and presence of chronic kidney disease (CKD) was performed retrospectively. Patient survival and cause of death were ascertained from computer records. Predictive models for (i) all-cause mortality (ACM) and (ii) breast cancer death (BCD) were built and then validated using bootstrap k-fold cross-validation. A comparison of predictive performance was made between a full cause-specific Cox model, a sub cause-specific Cox model, and a full Fine-Gray sub-distribution hazard model. Results1136 patients were included in the study. The median follow-up time was 6.2 years. 125 (11%) women died from breast cancer and 155 (14%) died from other causes. For the prediction of BCD, the cause-specific Cox sub-model performed the best. The time dependent AUC begins above 0.91 in year one to 3 reducing to 0.83 in year 6. The factors included in the Cox sub model were tumour size, skin thickening, source of detection, tumour grade, ER status, pre-operative nodal metastasis and CKD. ConclusionWe have shown that a model based on preoperative factors can predict BCD. Such prediction if externally validated and incorporating treatment data could be useful for treatment planning and patient counselling.

Prediction of recurrent stroke among ischemic stroke patients with atrial fibrillation: Development and validation of a risk score model.

There is currently no validated risk prediction model for recurrent events among patients with acute ischemic stroke (AIS) and atrial fibrillation (AF). Considering that the application of conventional risk scores has contextual limitations, new strategies are needed to develop such a model. Here, we set out to develop and validate a comprehensive risk prediction model for stroke recurrence in AIS patients with AF. AIS patients with AF were collected from multicenter registries in South Korea and Japan. A developmental dataset was constructed with 5648 registered cases from both countries for the period 2011‒2014. An external validation dataset was also created, consisting of Korean AIS subjects with AF registered between 2015 and 2018. Event outcomes were collected during 1 year after the index stroke. A multivariable prediction model was developed using the Fine-Gray subdistribution hazard model with non-stroke mortality as a competing risk. The model incorporated 21 clinical variables and was further validated, calibrated, and revised using the external validation dataset. The developmental dataset consisted of 4483 Korean and 1165 Japanese patients (mean age, 74.3 ± 10.2 years; male 53%); 338 patients (6%) had recurrent stroke and 903 (16%) died. The clinical profiles of the external validation set (n = 3668) were comparable to those of the developmental dataset. The c-statistics of the final model was 0.68 (95% confidence interval, 0.66 ‒0.71). The developed prediction model did not show better discriminative ability for predicting stroke recurrence than the conventional risk prediction tools (CHADS2, CHA2DS2-VASc, and ATRIA). Neither conventional risk stratification tools nor our newly developed comprehensive prediction model using available clinical factors seemed to be suitable for identifying patients at high risk of recurrent ischemic stroke among AIS patients with AF in this modern direct oral anticoagulant era. Detailed individual information, including imaging, may be warranted to build a more robust and precise risk prediction model for stroke survivors with AF.

Association between post-hospital clinic and telephone follow-up provider visits with 30-day readmission risk in an integrated health system

BackgroundFollow-up visits with clinic providers after hospital discharge may not be feasible for some patients due to functional limitations, transportation challenges, need for physical distancing, or fear of exposure especially during the current COVID-19 pandemic.MethodsThe aim of the study was to determine the effects of post-hospital clinic (POSH) and telephone (TPOSH) follow-up provider visits versus no visit on 30-day readmission. We used a retrospective cohort design based on data from 1/1/2017 to 12/31/2019 on adult patients (n = 213,513) discharged home from 15 Kaiser Permanente Southern California hospitals. Completion of POSH or TPOSH provider visits within 7 days of discharge was the exposure and all-cause 30-day inpatient and observation stay readmission was the primary outcome. We used matching weights to balance the groups and Fine-Gray subdistribution hazard model to assess for readmission risk.ResultsUnweighted all-cause 30-day readmission rate was highest for patients who completed a TPOSH (17.3%) followed by no visit (14.2%), non-POSH (evaluation and management visits that were not focused on the hospitalization: 13.6%) and POSH (12.6%) visits. The matching weighted models showed that the effects of POSH and TPOSH visits varied across patient subgroups. For high risk (LACE 11+) medicine patients, both POSH (HR: 0.77, 95% CI: 0.71, 0.85, P < .001) and TPOSH (HR: 0.91, 95% CI: 0.83, 0.99, P = .03) were associated with 23 and 9% lower risk of 30-day readmission, respectively, compared to no visit. For medium to low risk medicine patients (LACE< 11) and all surgical patients regardless of LACE score or age, there were no significant associations for either visit type with risk of 30-day readmission.ConclusionsPost-hospital telephone follow-up provider visits had only modest effects on 30-day readmission in high-risk medicine patients compared to clinic visits. It remains to be determined if greater use and comfort with virtual visits by providers and patients as a result of the pandemic might improve the effectiveness of these encounters.

Association between lung function and future risks of diabetes, asthma, myocardial infarction, hypertension and all-cause mortality.

BackgroundWhile forced expiratory volume in 1 s (FEV1) is a hallmark of disease progression in chronic obstructive lung diseases, little is known about the relationship between baseline FEV1 and future risks of other medical conditions.ObjectiveThe aim of this study was to investigate the association between baseline FEV1 and future risks of diabetes, asthma, myocardial infarction, hypertension and all-cause mortality.MethodsWe used data from the National Health and Nutrition Examination Survey and its Epidemiological Follow-Up Study. Our data provided longitudinal follow-up of the original cohort for up to 12 years. We used two competing risks approaches, the cause-specific hazard model and the Fine–Gray sub-distribution hazard model, to measure the associations between baseline FEV1 and future risks of the outcomes of interest. All models were adjusted for major confounding factors.ResultsThe final sample included 3020 participants (mean±sd baseline age 44.64±13.44 years). In the cause-specific hazard model, for every per cent increase in the baseline per cent predicted FEV1, the hazard of the event reduced by 2.5% (HR 0.975; 95% CI 0.958–0.994) for diabetes, 4.3% (HR 0.957; 95% CI 0.932–0.983) for asthma and 1.8% (HR 0.982; 95% CI 0.971–0.992) for all-cause mortality. There was no statistically significant association between baseline per cent predicted FEV1 and future risks of myocardial infarction (HR 0.987; 95% CI 0.970–1.004) and hypertension (HR 0.998; 95% CI 0.992–1.005). Consistent results were observed for the Fine–Gray sub-distribution hazard model.ConclusionOur data suggest that lower per cent predicted FEV1 values at baseline were significantly associated with higher future risks of diabetes, asthma and all-cause mortality.

The Israeli national policy for discontinuation of isolation of carbapenem-resistant Enterobacterales carriers by carbapenemase type: a retrospective cohort study

ObjectivesThe Israeli national policy for containing carbapenemase-producing Enterobacterales (CPE) includes a protocol allowing for discontinuation of carrier status following spontaneous decolonization. We examined the strategy's effectiveness based on carbapenemase type. MethodsWe performed a retrospective cohort study comparing individuals colonized with KPC- or NDM-producing Enterobacterales who underwent the process of isolation discontinuation. The primary outcome was reversion of carrier status, i.e. re-identification of the same CPE species following isolation discontinuation. We used survival analysis to estimate overall hazard ratio and performed competing-risks analysis using a Fine–Gray subdistribution hazard model and cause-specific hazard ratios. ResultsBetween 1 January 2006 and 1 January 2019 we identified 1694 individuals who met inclusion criteria, including 1337 (78.9%) carriers of KPC-producing Enterobacterales, 305 (18.0%) carriers of NDM-producing Enterobacterales and 52 (3.1%) carriers of dual KPC-/NDM-producing Enterobacterales. A total of 134 individuals (7.9%) had reversion of carrier status: 9.1% (121/1337) and 4.3% (13/305) of individuals with KPC- and NDM-producing Enterobacterales, respectively. The subdistribution hazard ratio of status reversion was not increased among carriers of NDM producers compared with KPC producers (0.567, 95% CI 0.320–1.000], p 0.052). Cause-specific hazard ratios yielded similar results (0.522, 95% CI 0.291–0.937, p 0.029. ConclusionsCarriage of NDM-producing Enterobacterales was not associated with higher rates of reversion to carrier status following spontaneous decolonization than was carriage of KPC-producing Enterobacterales.

Fine-Gray subdistribution hazard models to simultaneously estimate the absolute risk of different event types: Cumulative total failure probability may exceed 1.

The Fine‐Gray subdistribution hazard model has become the default method to estimate the incidence of outcomes over time in the presence of competing risks. This model is attractive because it directly relates covariates to the cumulative incidence function (CIF) of the event of interest. An alternative is to combine the different cause‐specific hazard functions to obtain the different CIFs. A limitation of the subdistribution hazard approach is that the sum of the cause‐specific CIFs can exceed 1 (100%) for some covariate patterns. Using data on 9479 patients hospitalized with acute myocardial infarction, we estimated the cumulative incidence of both cardiovascular death and non‐cardiovascular death for each patient. We found that when using subdistribution hazard models, approximately 5% of subjects had an estimated risk of 5‐year all‐cause death (obtained by combining the two cause‐specific CIFs obtained from subdistribution hazard models) that exceeded 1. This phenomenon was avoided by using the two cause‐specific hazard models. We provide a proof that the sum of predictions exceeds 1 is a fundamental problem with the Fine‐Gray subdistribution hazard model. We further explored this issue using simulations based on two different types of data‐generating process, one based on subdistribution hazard models and other based on cause‐specific hazard models. We conclude that care should be taken when using the Fine‐Gray subdistribution hazard model in situations with wide risk distributions or a high cumulative incidence, and if one is interested in the risk of failure from each of the different event types.