Cardiovascular Death Risk in Primary Central Nervous System Lymphoma Patients Treated With Chemotherapy: A Registry-Based Cohort Study

Long-term cardiovascular mortality risk in patients with bladder cancer: a real-world retrospective study of 129,765 cases based on the SEER database

Introduction

Among 28 cancer types, bladder cancer (BC) patients have the highest risk of dying from cardiovascular disease (CVD). We aimed to identify the independent risk factors and develop a novel nomogram for predicting long-term cardiovascular mortality in patients with BC.

Methods

We extracted data from the Surveillance, Epidemiology, and End Results (SEER) database for patients diagnosed with bladder cancer (BC) between 2000 and 2017. The cumulative incidence function (CIF) was computed for both CVD-related death and other causes of death. Then we performed univariate and multivariate analyses to explore the independent risk factors and further develop a novel nomogram to predict cardiovascular mortality at 5- and 10-year for patients with BC by using the Fine-Gray competing risk model. The efficacy of the developed nomogram was assessed by the concordance index (C-index), receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis (DCA).

Results

A total of 12,9765 patients were randomly divided into training (n = 90,835, 70%), and validation (n = 38,930, 30%) cohorts. During the follow-up period, 31,862 (46.4%) patients died from BC, and 36793 (53.6%) patients died from non-BC, of which CVD-related death accounted for 17,165 (46.7%), being the major cause of non-cancer deaths. The multivariate analysis showed that age, sex, race, marital status, histologic type, tumor grade, summary stage, and chemotherapy were independent risk factors of CVD-related death in BC patients. The nomogram based on the above eight factors showed good discrimination power, excellent consistency, and clinical practicability: (1) the areas under the curve of the ROC for 5- and 10-year CVD-related death of 0.725 and 0.732 in the training cohort and 0.726 and 0.734 in the validation cohort; (2) the calibration curves showed that the prediction probabilities were basically consistent with the observed probabilities; (3) the DCA curves revealed that the nomogram had high positive net benefits.

Discussion

To our knowledge, this was the first study to identify the independent risk factors and develop a novel nomogram for predicting long-term cardiovascular mortality in patients with BC based on the competing risk model. Our results could help clinicians comprehensively and effectively manage the co-patient of BC and CVD, thereby reducing the risk of cardiovascular mortality in BC survivors.

High risk of non-cancer mortality in bladder cancer patients: evidence from SEER-Medicaid

PURPOSE

The objective of this study was to investigate non-cancer causes of death and associated risk factors after bladder cancer (BC) diagnosis.

METHODS

Eligible BC patients were obtained from the SEER database. SEER*Stat software 8.3.9.2 was used to calculate the standardized mortality ratios (SMRs). The proportions of different non-cancer cause of death were calculated and analyzed in different follow-up periods. Multivariate competing risk model was used to analyze the risk factors for death of BC and non-cancer diseases.

RESULTS

In total, 240,954 BC patients were included and 106,092 patients experienced death, with 37,205 (35.07%), 13,208 (12.45%) and 55,679 (52.48%) patients experienced BC, other cancer and non-cancer disease-related deaths, respectively. Overall SMR for BC patients who died from non-cancer diseases was 2.42 (95% CI [2.40-2.44]). Cardiovascular diseases were the most common non-cancer cause of death, followed by respiratory diseases, diabetes mellitus, and infectious diseases. Multivariate competing risk analysis identified the following high-risk factors for non-cancer mortality: age > 60 years, male, whites, in situ stage, pathological type of transitional cell carcinoma, not receiving treatment (including surgery, chemotherapy, or radiation), and widowed.

CONCLUSIONS

Cardiovascular diseases are the leading non-cancer cause of death in BC patients, followed by respiratory disease, diabetes mellitus and infectious diseases. Physicians should pay attention to the risk of death from these non-cancer diseases. Also, physicians should encourage patients to engage in more proactive self-surveillance and follow up.

Non cancer causes of death after gallbladder cancer diagnosis: a population-based analysis

Mortality from non cancer causes in patients with gallbladder cancer (GBC) still unclear. This study evaluated the causes and risk factors of non cancer death during different follow-up periods after GBC diagnosis. Non cancer causes of death for GBC patients diagnosed between 2000 and 2017 in Surveillance, Epidemiology and End Results database were analyzed and standardized mortality rates (SMR) for each non cancer death were calculated. Predictors for non cancer death were identified through multivariate competing risk analysis. A total 11,927 GBC patients were identified for further analysis, 9393 died during follow up. The largest proportion of non cancer deaths occurred > 3 years after diagnosis (39.4%). Most common non cancer cause were cardiovascular disease (43.3%), followed by other cause of death (34.4%) and infectious diseases (8.6%). Compared with US general population, GBC patients has higher risk of death from disease of heart (SMR, 1.58; 95%CI, 1.41-1.75), septicemia (SMR,3.21; 95%CI, 2.27-4.40), diabetes mellitus (SMR,1.97; 95%CI, 1.43-2.63), alone with other causes. Non cancer causes accounted for a significant proportion of deaths during the follow-up period after GBC diagnosis. The risk of non cancer death is higher in GBC patients than in the general population. Our study provides comprehensive assessment of death from non cancer cause in GBC patients, which has important implications for health management in GBC patients.

Non-cancer-specific survival in patients with primary central nervous system lymphoma: A multi-center cohort study

Objective

The study aimed to evaluate the non-cancer-specific death risk and identify the risk factors affecting the non-cancer-specific survival (NCSS) in patients with primary central nervous system lymphoma (PCNSL).

Methods

This multi-center cohort study included 2497 patients with PCNSL in the Surveillance, Epidemiology and End Results (SEER) database from 2007 to 2016, with a mean follow-up of 4.54 years. The non-cancer-specific death risk in patients with PCNSL and primary central nervous system diffuse large B-cell lymphoma (PCNS-DLBCL) was evaluated using the proportion of deaths, standardized mortality ratio (SMR), and absolute excess risk (AER). Univariate and multivariate competing risk regression models were utilized to identify the risk factors of NCSS.

Results

PCNSL was the most frequent cause of death in PCNSL patients (75.03%). Non-cancer-specific causes constituted a non-negligible portion of death (20.61%). Compared with the general population, PCNSL patients had higher risks of death from cardiovascular disease (CVD) (SMR, 2.55; AER, 77.29), Alzheimer's disease (SMR, 2.71; AER, 8.79), respiratory disease (SMR, 2.12; AER, 15.63), and other non-cancer-specific diseases (SMR, 4.12; AER, 83.12). Male sex, Black race, earlier year of diagnosis (2007-2011), being unmarried, and a lack of chemotherapy were risk factors for NCSS in patients with PCNSL and PCNS-DLBCL (all P < 0.05).

Conclusion

Non-cancer-specific causes were important competing causes of death in PCNSL patients. More attention is recommended to non-cancer-specific causes of death in the management of PCNSL patients.

The Risk of Heart Disease-Related Death Among Anaplastic Astrocytoma Patients After Chemotherapy: A SEER Population-Based Analysis

Background

Despite improved overall survival outcomes, chemotherapy has brought concerns for heart disease–related death (HDRD) among cancer patients. The effect of chemotherapy on the risk of HDRD in anaplastic astrocytoma (AA) patients remains unclear.

Methods

We obtained 7,129 AA patients from the Surveillance, Epidemiology, and End Results (SEER) database from 1975 to 2016. Kaplan–Meier and Cox regression analysis were conducted to evaluate the effect of chemotherapy on the HDRD risk. Based on the competing risk model, we calculated the cumulative incidences of HDRD and non-HDRD and performed univariate and multivariate regression analyses. Then, a 1:1 propensity score matching (PSM) was used to improve the comparability between AA patients with and without chemotherapy. Landmark analysis at 216 and 314 months was employed to minimize immortal time bias.

Results

AA patients with chemotherapy were at a lower HDRD risk compared to those patients without chemotherapy (adjusted HR=0.782, 95%CI=0.736–0.83, P<0.001). For competing risk regression analysis, the cumulative incidence of HDRD in non-chemotherapy exceeded HDRD in the chemotherapy group (P<0.001) and multivariable analysis showed a lower HDRD risk in AA patients with chemotherapy (adjusted SHR=0.574, 95%CI=0.331–0.991, P=0.046). In the PSM-after cohort, there were no significant association between chemotherapy and the increased HDRD risk (adjusted SHR=0.595, 95%CI=0.316−1.122, P=0.11). Landmark analysis showed that AA patients who received chemotherapy had better heart disease–specific survival than those in the non-chemotherapy group (P=0.007) at the follow-up time points of 216 months. No difference was found when the follow-up time was more than 216 months.

Conclusion

AA patients with chemotherapy are associated with a lower risk of HDRD compared with those without chemotherapy. Our findings may help clinicians make a decision about the management of AA patients and provide new and important evidence for applying chemotherapy in AA patients as the first-line treatment. However, more research is needed to confirm these findings and investigate the correlation of the risk of HDRD with different chemotherapy drugs and doses.

Cardiovascular Outcomes in the Patients With Colorectal Cancer: A Multi-Registry-Based Cohort Study of 197,699 Cases in the Real World

Purpose

We aimed to investigate the mortality patterns and quantitatively assess the risks of cardiovascular death (CVD) in patients with colorectal cancer (CRC). We also established a competing-risk model to predict the probability of CVD for patients with CRC.

Patients and Methods

Patients with CRC who diagnosed between 2007 and 2015 in the Surveillance, Epidemiology, and End Results (SEER) database were included in the present study. The cumulative incidence function (CIF) was used for CVD and other causes of death, and Gray’s test was used to determine the subgroup difference in CIF. The Fine-Gray proportional subdistribution hazards model was used for identifying independent risk factors for CVD. A novel competing-risk model was established to evaluate the probability of CVD for patients with CRC. The performance of the nomogram was measured by concordance index (C-index), calibration curve, decision curve analysis (DCA), and risk stratification.

Results

After a median follow-up of 37.00 months, 79,455 deaths occurred, of whom 56,185 (70.71%) succumbed to CRC and 23,270 (29.29%) patients died due to non-CRC, among which CVD accounted for 9,702 (41.69%), being the major cause of non-cancer deaths. The 1-, 3-, and 5-year cumulative rates for CVD were 12.20, 24.25, and 30.51%, respectively. In multivariate analysis, age, race, marital status, tumor size, tumor stage, advanced stage, surgery, and chemotherapy were independent risk factors of CVD among patients with CRC. The nomogram was well calibrated and had good discriminative ability, with a c-index of 0.719 (95% CI, 0.738–0.742) in the training cohort and 0.719 (95% CI, 0.622–0.668) in the validation cohort. DCA demonstrated that nomogram produced more benefit within wide ranges of threshold probabilities for 1-, 3-, and 5-year CVD, respectively.

Conclusion

This study was the first to analyze the CIF and risk factors for CVD among CRC based on a competing-risk model. We have also built the first 1-, 3-, and 5-year competing nomogram for predicting CVD. This nomogram had excellent performance and could help clinicians to provide individualized management in clinical practice.