Prognostic factors for competing risk in patients with AIDS-related Kaposi's sarcoma: A SEER population-based study.

OBJECTIVES: Despite the improved survival of patients with AIDS and Kaposi's sarcoma (KS), competing events are a non-negligible issue affecting the survival of such patients. In this study, we explored the prognostic factors of KS-specific and non-KS-specific mortality in patients with AIDS-related KS (AIDS-KS), accounting for competing risk. METHODS: We identified 17 103 patients with AIDS-KS aged 18-65 years between 1980 and 2016 from the Surveillance, Epidemiology, and End Results (SEER) 18 registry database. Prognostic factors for KS-specific and non-KS-specific mortality were determined by the Fine and Grey proportional subdistribution hazard model. We built competing risk nomograms and assessed their predictive performance based on the identified prognostic factors. RESULTS: In total, 12 943 (75.68%) patients died, 1965 (15.50%) of whom died from competing events. The KS-specific mortality rate was 14 835 per 100 000 person-years, and the non-KS specific mortality rate was 2719 per 100 000 person-years. Specifically, age >44 years was associated with an 11% decrease in the subdistribution hazard of KS-specific mortality compared with age <43 years but a 50% increase in the subdistribution hazard of non-KS-specific mortality. Being male was associated with a 26% increase in the subdistribution hazard of KS-specific mortality compared with being female but a 32% decrease in the subdistribution hazard of non-KS-specific mortality. Notably, being in the antiretroviral therapy (ART) era consistently showed a decrease in the subdistribution hazard of both KS-specific and non-KS-specific mortality than being in the pre-ART era. CONCLUSIONS: Competing events commonly occurred among patients with AIDS-KS, which deserves further attention to improve the prognosis of these patients.

Fracture risk assessment in the presence of competing risk of death.

PURPOSE: To identify the optimal statistical approach for predicting the risk of fragility fractures in the presence of competing event of death. METHODS: We used real-world data from the Dubbo Osteoporosis Epidemiology Study that has monitored 3035 elderly participants for bone health and mortality. Fragility fractures were ascertained radiologically. Mortality was confirmed by the State Registry. We considered four statistical models for predicting fracture risk: (i) conventional Cox's proportional hazard model, (ii) cause-specific model, (iii) Fine-Gray sub-distribution model, and (iv) multistate model. These models were fitted and validated in the development (60% of the original sample) and validation (40%) subsets, respectively. The model performance was assessed by discrimination and calibration analyses. RESULTS: During a median follow-up of 11.3 years (IQR: 7.2, 16.2), 628 individuals (34.5%) in the development cohort fractured, and 630 (34.6%) died without a fracture. Neither the discrimination nor the 5-year prediction performance was significantly different among the models, though the conventional model tended to overestimate fracture risk (calibration-in-the-large index = - 0.24; 95% CI: - 0.43, - 0.06). For 10-year risk prediction, the multistate model (calibration-in-the-large index = - 0.05; 95% CI: - 0.20, 0.10) outperformed the cause-specific (- 0.23; - 0.30, - 0.08), Fine-Gray (- 0.31; - 0.46, - 0.16), and conventional model (- 0.54; - 0.70, - 0.39) which significantly overestimated fracture risk. CONCLUSION: Adjustment for competing risk of death has minimum impact on the short-term prediction of fracture. However, the multistate model yields the most accurate prediction of long-term fracture risk and should be considered for predictive research in the elderly, who are also at high mortality risk. Fracture risk assessment might be compromised by the competing event of death. This study, using real-world data found a multistate model was superior to the current competing risk methods in fracture risk assessment. A multistate model is considered an optimal statistical method for predictive research in the elderly.

Association of stress hyperglycemia ratio with in-hospital new-onset atrial fibrillation and long-term outcomes in patients with acute myocardial infarction.

AIMS: To investigate the predictive value and prognostic impact of stress hyperglycemia ratio (SHR) for new-onset atrial fibrillation (NOAF) complicating acute myocardial infarction (AMI). MATERIALS AND METHODS: This retrospective study included 2145 AMI patients without AF history between February 2014 and March 2018. SHR was calculated using fasting blood glucose (mmol/L)/[1.59*HbA1c (%)-2.59]. The association between SHR and post-MI NOAF was assessed with multivariable logistic regression analyses. The primary outcome was a composite of cardiac death, heart failure hospitalisation, recurrent MI, and ischaemic stroke (MACE). Cox regression-adjusted hazard ratios with 95% confidence intervals (CI) were estimated for MACE. RESULTS: A total of 245 (11.4%) patients developed NOAF. In the multivariable logistic regression analyses, SHR (each 10% increase) was significantly associated with increased risks of NOAF in the whole population (OR: 1.05, 95% CI: 1.01-1.10), particularly in non-diabetic individuals (OR:1.08, 95% CI: 1.01-1.17). During a median follow-up of 2.7 years, 370 (18.5%) MACEs were recorded. The optimal cut-off value of SHR for MACE prediction was 1.119. Patients with both high SHR (≥1.119) and NOAF possessed the highest risk of MACE compared to those with neither high SHR nor NOAF after multivariable adjustment (HR: 2.18, 95% CI: 1.39-3.42), especially for diabetics (HR: 2.63, 95% CI: 1.41-4.91). Similar findings were observed using competing-risk models. CONCLUSIONS: SHR is an independent predictor of post-MI NOAF in non-diabetic individuals. Diabetic patients with both high SHR and NOAF had the highest risk of MACE, suggesting that therapies targeting SHR may be considered in these patients. TRIAL REGISTRATION: ClinicalTrials.gov, NCT03533543.

Impact of age >70 years on oncological outcomes in patients with non-muscle-invasive bladder cancer treated with Bacillus Calmette-Guérin.

OBJECTIVE: To evaluate the impact of age on oncological outcomes in a large contemporary cohort of patients with non-muscle-invasive bladder cancer (NMIBC) treated with adequate Bacillus Calmette-Guérin (BCG). PATIENTS AND METHODS: We performed an Institutional Review Board-approved retrospective study analysing patients with NMIBC treated with adequate BCG at our institution from 2000 to 2020. Adequate BCG was defined as per United States Food and Drug Administration (FDA) guidelines as being receipt of at least five of six induction BCG instillations with a minimum of two additional doses (of planned maintenance or of re-induction) of BCG instillations within a span of 6 months. The study's primary outcome was to determine if age >70 years was associated with progression to MIBC cancer or distant metastasis. The cumulative incidence method and the competing-risk regression analyses were used to investigate the association of advanced age (>70 years) with progression, high-grade (HG) recurrence and cancer-specific mortality (CSM). RESULTS: Overall, data from 632 patients were analysed: 355 patients (56.2%) were aged ≤70 years and 277 (43.8%) were >70 years. Age >70 years did not adversely affect either cumulative incidence of progression or HG recurrence (P = 0.067 and P = 0.644, respectively). On competing-risk regression analyses, age >70 years did not emerge as an independent predictor of progression or HG recurrence (sub-standardised hazard ratio [SHR] 1.57, 95% confidence interval [CI] 0.87-2.81, P = 0.134; and SHR 1.05, 95% CI 0.77-1.44, P = 0.749). Not unexpectedly, patients in the older group did have higher overall mortality (P < 0.001) but not CSM (P = 0.057). CONCLUSION: Age >70 years was not associated with adverse oncological outcomes in a large contemporary cohort of patients receiving adequate intravesical BCG for NMIBC. BCG should not be withheld from older patients seeking for bladder sparing options.

The importance of considering competing risks in recurrence analysis of intracranial meningioma.

BACKGROUND: The risk of recurrence is overestimated by the Kaplan-Meier method when competing events, such as death without recurrence, are present. Such overestimation can be avoided by using the Aalen-Johansen method, which is a direct extension of Kaplan-Meier that accounts for competing events. Meningiomas commonly occur in older individuals and have slow-growing properties, thereby warranting competing risk analysis. The extent to which competing events are considered in meningioma literature is unknown, and the consequences of using incorrect methodologies in meningioma recurrence risk analysis have not been investigated. METHODS: We surveyed articles indexed on PubMed since 2020 to assess the usage of competing risk analysis in recent meningioma literature. To compare recurrence risk estimates obtained through Kaplan-Meier and Aalen-Johansen methods, we applied our international database comprising ~ 8,000 patients with a primary meningioma collected from 42 institutions. RESULTS: Of 513 articles, 169 were eligible for full-text screening. There were 6,537 eligible cases from our PERNS database. The discrepancy between the results obtained by Kaplan-Meier and Aalen-Johansen was negligible among low-grade lesions and younger individuals. The discrepancy increased substantially in the patient groups associated with higher rates of competing events (older patients with high-grade lesions). CONCLUSION: The importance of considering competing events in recurrence risk analysis is poorly recognized as only 6% of the studies we surveyed employed Aalen-Johansen analyses. Consequently, most of the previous literature has overestimated the risk of recurrence. The overestimation was negligible for studies involving low-grade lesions in younger individuals; however, overestimation might have been substantial for studies on high-grade lesions.

Assessing the influence of graft loss on 4-year patient survival after simultaneous pancreas-kidney transplantation: Kaplan-Meier versus Competing Risk Analysis model.

BACKGROUND: Graft loss increases the risk of patient death after simultaneous pancreas-kidney (SPK) transplantation. The relative risk of each graft failure is complex due to the influence of several competing events. METHODS: This retrospective, single-center study compared 4-year patient survival according to the graft status using Kaplan-Meier (KM) and Competing Risk Analysis (CRA). Patient survival was also assessed according to five eras (Era 1: 2001-2003; Era 2: 2004-2006; Era 3: 2007-2009; Era 4: 2010-2012; Era 5: 2012-2015). RESULTS: Between 2000 and 2015, 432 SPK transplants were performed. Using KM, patient survival was 86.5% for patients without graft loss (n = 333), 93.4% for patients with pancreas graft loss (n = 46), 43.7% for patients with kidney graft loss (n = 16), and 25.4% for patients with pancreas and kidney graft loss (n = 37). Patient survival was underestimated using KM versus CRA methods in patients with pancreas and kidney graft losses (25.4% vs. 36.2%), respectively. Induction with lymphocyte depleting antibodies was associated with 81% reduced risk (HR.19, 95% CI.38-.98, p = .0048), while delayed kidney function (HR 2.94, 95% CI 1.09-7.95, p = .033) and surgical complications (HR 2.94, 95% CI 1.22-7.08, p = .016) were associated with higher risk of death. Four-year patient survival increased from Era 1 to Era 5 (79% vs. 87.9%, p = .047). CONCLUSION: In this cohort of patients, kidney graft loss, with or without pancreas graft loss, was associated with higher mortality after SPK transplantation. Compared to CRA, the KM model underestimated survival only among patients with pancreas and kidney graft losses. Patient survival increased over time.

Impact of malnutrition on cancer recurrence, colorectal cancer-specific death, and non-colorectal cancer-related death in patients with colorectal cancer who underwent curative surgery.

AIM: This study aimed to examine how malnutrition, as reflected by the Geriatric Nutritional Risk Index (GNRI), is associated with colorectal cancer (CRC) recurrence and cause of death. METHODS: Consecutive stage I-III CRC patients (n = 601) were divided into two groups using GNRI 98 as the cutoff. The relationship of GNRI with overall survival (OS) and recurrence-free survival (RFS) was evaluated, followed by competing risk analysis to determine prognostic factors of non-CRC-related death, and hazard function analysis to examine changes in the risk of recurrence and death. RESULTS: Median body mass index was lower in the low GNRI group than in the high GNRI group (19.8 vs. 23.5; p < 0.001). After adjusting for known prognostic factors, a low GNRI was independently associated with reduced OS/RFS, and was a significant predictor of non-CRC-related death. The risk of recurrence was higher and peaked earlier in the low GNRI group than in the high GNRI group, although after 3 years, both groups had a similar risk. Meanwhile, the low GNRI group had a higher risk of non-CRC-related death over the course of 5 years. CONCLUSION: It is important to consider preoperative nutritional status along with the cancer stage when developing strategies to improve outcomes for CRC patients.

Editor's Choice -- Survival, Limb Salvage, and Management of Patients with Lower Limb Acute Ischaemia: A French National Retrospective Observational Study.

OBJECTIVE: The aim was to describe the baseline characteristics of French patients referred with acute limb ischaemia (ALI), and their clinical management and outcome (death, amputation). METHODS: This retrospective observational cohort study used the National Health Data System. All adults hospitalised for ALI who underwent revascularisation with an endovascular or open surgical approach between 1 January 2015 and 31 December 2020 were included and followed up until death or the end of the study (31 December 2021). A one year look back period was used to capture patients' medical history. The risks of death, and major and minor amputations were described using Kaplan-Meier and Aalen-Johansen estimators. A Cox model was used to report the adjusted association between groups and risk of death and Fine-Gray models for the risk of amputations considering the competing risk of death. RESULTS: Overall, 51 390 patients (median age 70 years, 69% male) were included and had a median follow up of 2.7 years: 39 411 (76.7%) were treated with an open approach and 11 979 (23.3%) with a percutaneous endovascular approach. The preferred approach for the revascularisation varied between French regions. The one year overall survival was 78.0% and 85.2% in the surgery and endovascular groups, respectively. The surgery group had a higher risk of death (hazard ratio [HR] 1.17, 95% CI 1.12 - 1.21), a higher risk of major amputation (sub-distribution HR 1.20, 95% CI 1.10 - 1.30) and lower risk of minor amputation (sub-distribution HR 0.66, 95% CI 0.60 - 0.71) than the endovascular group. Diabetes and dialysis increased the risk of major amputation by 52% and 78%, respectively. Subsequent ALI was the third most common cause of hospital re-admission within one year. CONCLUSION: ALI remains a condition at high risk of death and amputation. Individual risk factors and ALI severity need to be considered to choose between approaches. Continued prevention efforts, improved management, and access to the most suitable approach are necessary.

The role of marital status in gallbladder cancer: a real-world competing risk analysis.

BACKGROUND: The association between marital status and gallbladder cancer (GBC) remains uncertain. This study aimed to verify the relationship between marital status and GBC and construct a prognostic nomogram to predict the impact of marital status on GBC patients. METHOD: GBC patients were divided into married and unmarried groups using data from the Surveillance, Epidemiology, and End Results (SEER) database. We employed competing risk analyses, propensity score matching (PSM), and Kaplan-Meier survival analyses. The relationship between marital status and GBC was then verified, and the predicted nomogram was constructed. RESULTS: A total of 3913 GBC patients were obtained from the SEER database, and an additional 76 GBC patients from Hangzhou Traditional Chinese Medicine Hospital were selected as the external validation group. The competing risk analysis revealed a significant disparity in the 5-year cumulative incidence of cancer-specific death (CSD) between the two cohorts (59.1% vs. 65.2%, p = 0.003). Furthermore, the multivariate competing hazards regression analysis identified a significant association (HR, 1.17; 95% CI, 1.04-1.31; p = 0.007) between marital status and CSD. To assess the 1-, 3-, and 5-year risks of CSD, a comprehensive competing event nomogram was constructed using factors derived from the multivariate analysis. The area under the receiver operating characteristic curve (AUC) values for the 1-, 3-, and 5-year training cohorts were 0.806, 0.785, and 0.776, respectively. In the internal validation cohort, these values were 0.798, 0.790, and 0.790, while the external validation cohort exhibited AUC values of 0.748, 0.835, and 0.883 for the corresponding time intervals. Furthermore, calibration curves demonstrated a commendable level of concordance between the observed and predicted probabilities of CSD. CONCLUSION: Marriage was a protective factor for GBC patients after taking competing risk into consideration. The proposed nomogram demonstrated exceptional predictive power.

Competing risk analysis to estimate amputation incidence and risk in lower-extremity peripheral artery disease.

Background: Patients with peripheral artery disease face high amputation and mortality risk. When assessing vascular outcomes, consideration of mortality as a competing risk is not routine. We hypothesize standard time-to-event methods will overestimate major amputation risk in chronic limb-threatening ischemia (CLTI) and non-CLTI. Methods: Patients undergoing peripheral vascular intervention from 2017 to 2018 were abstracted from the Vascular Quality Initiative registry and stratified by mean age (⩾ 75 vs < 75 years). Mortality and amputation data were obtained from Medicare claims. The 2-year cumulative incidence function (CIF) and risk of major amputation from standard time-to-event analysis (1 - Kaplan-Meier and Cox regression) were compared with competing risk analysis (Aalen-Johansen and Fine-Gray model) in CLTI and non-CLTI. Results: A total of 7273 patients with CLTI and 5095 with non-CLTI were included. At 2-year follow up, 13.1% of patients underwent major amputation and 33.4% died without major amputation in the CLTI cohort; 1.3% and 10.7%, respectively, in the non-CLTI cohort. In CLTI, standard time-to-event analysis overestimated the 2-year CIF of major amputation by 20.5% and 13.7%, respectively, in patients ⩾ 75 and < 75 years old compared with competing risk analysis. The standard Cox regression overestimated adjusted 2-year major amputation risk in patients ⩾ 75 versus < 75 years old by 7.0%. In non-CLTI, the CIF was overestimated by 7.1% in patients ⩾ 75 years, and the adjusted risk was overestimated by 5.1% compared with competing risk analysis. Conclusions: Standard time-to-event analysis overestimates the incidence and risk of major amputation, especially in CLTI. Competing risk analyses are alternative approaches to estimate accurately amputation risk in vascular outcomes research.

Analysis of the survival time of patients with heart failure with reduced ejection fraction: a Bayesian approach via a competing risk parametric model.

PURPOSE: Heart failure (HF) is a widespread ailment and is a primary contributor to hospital admissions. The focus of this study was to identify factors affecting the extended-term survival of patients with HF, anticipate patient outcomes through cause-of-death analysis, and identify risk elements for preventive measures. METHODS: A total of 435 HF patients were enrolled from the medical records of the Rajaie Cardiovascular Medical and Research Center, covering data collected between March and August 2018. After a five-year follow-up (July 2023), patient outcomes were assessed based on the cause of death. The survival analysis was performed with the AFT method with the Bayesian approach in the presence of competing risks. RESULTS: Based on the results of the best model for HF-related mortality, age [time ratio = 0.98, confidence interval 95%: 0.96-0.99] and ADHF [TR = 0.11, 95% (CI): 0.01-0.44] were associated with a lower survival time. Chest pain in HF-related mortality [TR = 0.41, 95% (CI): 0.10-0.96] and in non-HF-related mortality [TR = 0.38, 95% (CI): 0.12-0.86] was associated with a lower survival time. The next significant variable in HF-related mortality was hyperlipidemia (yes): [TR = 0.34, 95% (CI): 0.13-0.64], and in non-HF-related mortality hyperlipidemia (yes): [TR = 0.60, 95% (CI): 0.37-0.90]. CAD [TR = 0.65, 95% (CI): 0.38-0.98], CKD [TR = 0.52, 95% (CI): 0.28-0.87], and AF [TR = 0.53, 95% (CI): 0.32-0.81] were other variables that were directly related to the reduction in survival time of patients with non-HF-related mortality. CONCLUSION: The study identified distinct predictive factors for overall survival among patients with HF-related mortality or non-HF-related mortality. This differentiated approach based on the cause of death contributes to the estimation of patient survival time and provides valuable insights for clinical decision-making.

Using multistate models with clinical trial data for a deeper understanding of complex disease processes.

A clinical trial represents a large commitment from all individuals involved and a huge financial obligation given its high cost; therefore, it is wise to make the most of all collected data by learning as much as possible. A multistate model is a generalized framework to describe longitudinal events; multistate hazards models can treat multiple intermediate/final clinical endpoints as outcomes and estimate the impact of covariates simultaneously. Proportional hazards models are fitted (one per transition), which can be used to calculate the absolute risks, that is, the probability of being in a state at a given time, the expected number of visits to a state, and the expected amount of time spent in a state. Three publicly available clinical trial datasets, colon, myeloid, and rhDNase, in the survival package in R were used to showcase the utility of multistate hazards models. In the colon dataset, a very well-known and well-used dataset, we found that the levamisole+fluorouracil treatment extended time in the recurrence-free state more than it extended overall survival, which resulted in less time in the recurrence state, an example of the classic "compression of morbidity." In the myeloid dataset, we found that complete response (CR) is durable, patients who received treatment B have longer sojourn time in CR than patients who received treatment A, while the mutation status does not impact the transition rate to CR but is highly influential on the sojourn time in CR. We also found that more patients in treatment A received transplants without CR, and more patients in treatment B received transplants after CR. In addition, the mutation status is highly influential on the CR to transplant transition rate. The observations that we made on these three datasets would not be possible without multistate models. We want to encourage readers to spend more time to look deeper into clinical trial data. It has a lot more to offer than a simple yes/no answer if only we, the statisticians, are willing to look for it.

Three-year incidence and acute setting predictors of epilepsy after neonatal and childhood arterial ischaemic stroke: a disease-based cohort study.

To assess the association between clinical and MRI characteristics of arterial ischaemic stroke (AIS) and the 3-year risk of post-stroke epilepsy (PSE) in paediatric patients. Retrospective cohort study. Database from a single tertiary referral centre for paediatric stroke in Chile. Two hundred seven neonates and children (1 day to 18 years) with a first-ever supratentorial AIS diagnosed between January 2003 and December 2019 were evaluated. Diagnosis of PSE and explanatory variables were consecutively recorded from hospital inpatient and annual outpatient records in a predesigned database. Competing risk analysis (competing events: death and loss to follow-up) of multiple Cox proportional hazards regression was performed to estimate adjusted subhazard ratios (SHRs) of PSE. Confidence intervals (95% CI) were calculated using bootstrap resampling (1000 replications). Interaction terms were added to investigate moderating effects. The 3-year incidence rate of PSE was 166.5 per 1000 person-years (neonatal: 150.1; childhood: 173.9). The 3-year cumulative incidence was 33%. Patients with acute symptomatic non-status seizures (SHR = 3.13; 95% CI = 1.43-6.82), status epilepticus (SHR = 5.16; 95% CI = 1.90-13.96), abnormal discharge neurological status (SHR = 2.52; 95% CI = 1.12-5.63), cortical lesions (SHR = 2.93; 95% CI = 1.48-5.81), and multifocal infarcts with stroke size < 5% of supratentorial brain volume (SHR = 3.49; 95% CI = 1.44-8.46) had a higher risk of PSE. CONCLUSION: This study identified specific and reliable acute clinical and imaging predictors of PSE in paediatric patients, helping clinicians identify high-risk patients with potential implications for treatment decisions. WHAT IS KNOWN: • Numerous risk factors have been proposed for post-stroke epilepsy, but there is a lack of studies evaluating these variables while accounting for confounding factors and competing risks over time. WHAT IS NEW: • After adjustment for competing events, acute symptomatic seizures, both non-status and status epilepticus, abnormal mental status or motor neurological examination at hospital discharge, cortical involvement, and multifocal ischaemic lesions in small strokes are all independent predictors of post-stroke epilepsy. • Knowing the predictors of post-stroke epilepsy is essential for clinicians to make well-informed and effective decisions about treatment.

Association of radioactive iodine treatment in differentiated thyroid cancer and cardiovascular death: a large population-based study.

PURPOSE: The risk of cardiovascular diseases' death (CVD) in patients with differentiated thyroid cancer (DTC) treated with radioactive iodine (RAI) after surgery has not been adequately studied. METHODS: Data of DTC patients who received RAI after surgery were retrieved from the Surveillance, Epidemiology, and End Result (SEER) database (2004-2015). Standardized mortality rate (SMR) analysis was used to evaluate the CVD risk in patients with RAI vs general population. A 1:1 propensity score matching (PSM) was applied to balance inter-group bias, and Pearson's correlation coefficient was used to detect collinearity between variables. The Cox proportional hazard model and multivariate competing risk model were utilized to evaluate the impact of RAI on CVD. At last, we curved forest plots to compare differences in factors significantly associated with CVD or cancer-related deaths. RESULTS: DTC patients with RAI treatment showed lower SMR for CVD than general population (RAI: SMR = 0.66, 95% CI 0.62-0.71, P < 0.05). After PSM, Cox proportional hazard regression demonstrated a decreased risk of CVD among patients with RAI compared to patients without (HR = 0.76, 95% CI 0.6-0.97, P = 0.029). However, in competing risk regression analysis, there was no significant difference (adjusted HR = 0.82, 95% CI 0.66-1.01, P = 0.11). The independent risk factors associated with CVD were different from those associated with cancer-related deaths. CONCLUSION: The CVD risk between DTC patients treated with RAI and those who did not was no statistical difference. Noteworthy, they had decreased CVD risk compared with the general population.

Competing risk nomogram and risk classification system for evaluating overall and cancer-specific survival in neuroendocrine carcinoma of the cervix: a population-based retrospective study.

OBJECTIVE: Neuroendocrine carcinoma of the cervix (NECC) is a rare malignancy with poor clinical prognosis due to limited therapeutic options. This study aimed to establish a risk-stratification score and nomogram models to predict prognosis in NECC patients. METHODS: Data on individuals diagnosed with NECC between 2000 and 2019 were retrieved from the Surveillance Epidemiology and End Results (SEER) database and then randomly classified into training and validation cohorts (7:3). Univariate and multivariate Cox regression analyses evaluated independent indicators of prognosis. Least absolute shrinkage and selection operator (LASSO) regression analysis further assisted in confirming candidate variables. Based on these factors, cancer-specific survival (CSS) and overall survival (OS) nomograms that predict survival over 1, 3, and 5 years were constructed. The receiver operating characteristic (ROC) curve, the concordance index (C-index), and the calibration curve estimated the precision and discriminability of the competing risk nomogram for both cohorts. Finally, we assessed the clinical value of the nomograms using decision curve analysis (DCA). RESULTS: Data from 2348 patients were obtained from the SEER database. Age, tumor stage, T stage, N stage, chemotherapy, radiotherapy, and surgery predicted OS. Additionally, histological type was another standalone indicator of CSS prognosis. For predicting CSS, the C-index was 0.751 (95% CI 0.731 ~ 0.770) and 0.740 (95% CI 0.710 ~ 0.770) for the training and validation cohorts, respectively. Furthermore, the C-index in OS prediction was 0.757 (95% CI 0.738 ~ 0.776) and 0.747 (95% CI 0.718 ~ 0.776) for both cohorts. The proposed model had an excellent discriminative ability. Good accuracy and discriminability were also demonstrated using the AUC and calibration curves. Additionally, DCA demonstrated the high clinical potential of the nomograms for CSS and OS prediction. We constructed a corresponding risk classification system using nomogram scores. For the whole cohort, the median CSS times for the low-, moderate-, and high-risk groups were 59.3, 19.5, and 7.4 months, respectively. CONCLUSION: New competing risk nomograms and a risk classification system were successfully developed to predict the 1-, 3-, and 5-year CSS and OS of NECC patients. The models are internally accurate and reliable and may guide clinicians toward better clinical decisions and the development of personalized treatment plans.

Effect of marital status on the survival outcomes of cervical cancer: a retrospective cohort study based on SEER database.

BACKGROUND: Cervical cancer is the fourth most common malignant tumor troubling women worldwide. Whether marital status affects the prognosis of cervical cancer is still unclear. Here, we investigate the prognostic value of marital status in patients with cervical cancer based on the seer database. MATERIAL/METHODS: The demographic and clinical data of patients with cervical cancer were extracted from the Surveillance, Epidemiology, and End Results (SEER) database from 1975 to 2017. Patients were divided into two groups (married and unmarried) according to marital status, and then the clinical characteristics of each group were compared using the chi-square test. Propensity score matching (PSM) was used to reduce differences in baseline characteristics. The overall survival (OS) and cervical cancer-specific survival (CCSS) were assessed by the Kaplan-Meier method, univariate and multivariate Cox regression models, and stratified analysis. Moreover, univariate and multivariate competing risk regression models were performed to calculate hazard ratios (HR) of death risk. RESULTS: A total of 21,148 patients were included in this study, including 10,603 married patients and 10,545 unmarried patients. Married patients had better OS(P < 0.05) and CCSS (P < 0.05) compared to unmarried patients, and marital status was an independent prognostic factor for both OS (HR: 0.830, 95% CI: 0.798-0.862) and CCSS (HR: 0.892, 95% CI: 0.850-0.937). Moreover, after eliminating the competing risk, married patients (CCSD: HR:0.723, 95% CI: 0.683-0.765, P < 0.001) had a significantly decreased risk of death compared to unmarried patients. In stratified analysis, the married patients showed better OS and CCSS than the unmarried patients diagnosed in 1975-2000 and 2001-2017. CONCLUSIONS: Being married was associated with a favorable prognosis of cervical cancer, and marital status was an independent prognostic factor for cervical cancer.

High cardiovascular mortality risk among older merkel cell carcinoma patients.

OBJECTIVE: Previous research has primarily focused on the incidence and mortality rates of Merkel cell carcinoma (MCC), neglecting the examination of cardiovascular mortality (CVM) risk among survivors, particularly older patients. This study aims to assess the risk of CVM in older individuals diagnosed with MCC. METHODS: Data pertaining to older MCC patients were obtained from the Surveillance, Epidemiology, and End Results database (SEER). CVM risk was measured using standardized mortality ratio (SMR) and cumulative mortality. Multivariate Fine-Gray's competing risk model was utilized to evaluate the risk factors contributing to CVM. RESULTS: Among the study population of 2,899 MCC patients, 465 (16.0%) experienced CVM during the follow-up period. With the prolongation of the follow-up duration, the cumulative mortality rate for CVM reached 27.36%, indicating that cardiovascular disease (CVD) became the second most common cause of death. MCC patients exhibited a higher CVM risk compared to the general population (SMR: 1.69; 95% CI: 1.54-1.86, p < 0.05). Notably, the SMR for other diseases of arteries, arterioles, and capillaries displayed the most significant elevation (SMR: 2.69; 95% CI: 1.16-5.29, p < 0.05). Furthermore, age at diagnosis and disease stage were identified as primary risk factors for CVM, whereas undergoing chemotherapy or radiation demonstrated a protective effect. CONCLUSION: This study emphasizes the significance of CVM as a competing cause of death in older individuals with MCC. MCC patients face a heightened risk of CVM compared to the general population. It is crucial to prioritize cardiovascular health starting from the time of diagnosis and implement personalized CVD monitoring and supportive interventions for MCC patients at high risk. These measures are essential for enhancing survival outcomes.

Assessment of prognostic factors in patients with primary ocular adnexal lymphoma when considering competing risk elements.

BACKGROUND: Accurate prognostic factors for primary ocular adnexal lymphoma (POAL) are scarce. Survival models and prognostic factors derived without considering competing risk factors suffer from major statistical errors. This study aimed to accurately assess prognostic factors in POAL patients using competing risk models, and compare this to the traditional COX proportional hazards model. METHODS: This retrospective study utilised data from the Surveillance, Epidemiology, and End Results (SEER) program 2010-2015 and included patients with B-cell POAL. The cumulative incidence function and Gray's test for cause-specific survival were calculated as univariate analysis. The competing risk models were a Fine-Gray subdistribution hazard model and a cause-specific model, and a traditional COX model was employed as a multivariate analysis. RESULTS: This study enrolled 846 eligible patients with POAL: 60 patients (7.09%) died from POAL and 123 patients (14.54%) died from other causes. Multivariate competing risk models indicated that age, laterality, histology subtype, the 7th edition of American Joint Committee on Cancer stage T, and radiotherapy were independent predictors for cause-specific survival of patients with POAL. There was high consistency between the two competing risk models. The COX model made several misestimations on the statistical significance and hazard ratios of prognostic factors. CONCLUSIONS: This study established competing risk models as a method to assess POAL prognostic factors, which was more accurate than traditional methods that do not consider competing risk elements.

Development and validation of a nomogram for predicting specific mortality risk: A study of competing risk model based on real endometrial cancer patients.

OBJECTIVE: This study aimed to construct a competing risk prediction model for predicting specific mortality risks in endometrial cancer patients from the SEER database based on their demographic characteristics and tumor information. METHODS: We collected relevant clinical data on patients with histologically confirmed endometrial cancer in the SEER database between 2010 and 2015. Univariate and multivariate competing risk models were used to analyze the risk factors for endometrial cancer-specific death, and a predictive nomogram was constructed. C-index and receiver operating characteristic curve (ROC) at different time points were used to verify the accuracy of the constructed nomogram. RESULTS: There were 26 109 eligible endometrial cancer patients in the training cohort and 11 189 in the validation cohort. Univariate and multivariate analyses revealed that Age, Marriage, Grade, Behav, FIGO, Size, Surgery, SurgOth, Radiation, ParaAortic_Nodes, Peritonea, N positive, DX_liver, and DX_lung were independent prognostic factors for specific mortality in endometrial cancer patients. Based on these factors, a nomogram was constructed. Internal validation showed that the nomogram had a good discriminative ability (C-index = 0.883 [95% confidence interval [CI]: 0.881-0.884]), and the 1-, 3-, and 5-year AUC values were 0.901, 0.886 and 0.874, respectively. External validation indicated similar results (C-index = 0.883 [95%CI: 0.882-0.883]), and the 1-, 3-, and 5- AUC values were 0.908, 0.885 and 0.870, respectively. CONCLUSION: We constructed a competing risk model to predict the specific mortality risk among endometrial cancer patients. This model has favorable accuracy and reliability and can provide a reference for the development and update of endometrial cancer prognostic risk assessment tools.

Upfront surgery versus definitive radiotherapy: competing risk analyses for cancer-specific and noncancer mortality in oropharyngeal cancer.

PURPOSE: The optimal treatment strategy for oropharyngeal cancer (OPC) is undetermined. We aim to compare the survival outcomes of OPC patients treated with upfront surgery versus definitive radiotherapy (RT). METHODS: A total of 8057 cases were retrieved from the Surveillance, Epidemiology, and End Results database. Primary endpoints were cancer-specific and noncancer mortalities, which were estimated using cumulative incidence function and compared by Gray's test. Univariate and multivariate Fine-Gray subdistribution hazard models were used to estimate the effects of treatment modality on mortality. Subgroup analyses were performed in propensity-score-matched cohorts. All the analyses were conducted separately in human papillomavirus (HPV)-negative and HPV-positive cohorts. RESULTS: In the HPV-negative cohort, definitive RT was independently associated with increased risk of cancer-specific mortality (adjusted subdistribution hazard ratio [SHR], 1.31; 95% confidence interval [CI], 1.05-1.64; P = 0.017) and noncancer mortality (adjusted SHR, 1.59; 95% CI 1.13-2.25; P = 0.008). In the HPV-positive cohort, definitive RT was independently associated with increased risk of cancer-specific mortality (adjusted SHR, 1.51; 95% CI 1.23-1.85; P < 0.001) and noncancer mortality (adjusted SHR, 1.53; 95% CI 1.11-2.12; P = 0.009). CONCLUSION: Upfront surgery is a superior treatment modality compared with definitive RT in terms of lowering cancer-specific and noncancer mortality in OPC patients, regardless of HPV status. Further prospective clinical trials are needed to confirm our findings.