Causes of Death and Conditional Survival Estimates of Medium- and Long-term Survivors of Pancreatic Adenocarcinoma

Conditional Relative Survival of Exocrine Pancreatic Cancer: A Population-Based Study

BACKGROUND

Adjusted prognostic information is important for treatment decisions, especially in elderly patients or survivors of exocrine pancreatic cancer (EPC). This study aims to investigate conditional relative survival (CS) rates and conditional probabilities of death in patients with EPC.

METHODS

Data of 77,975 individuals diagnosed with EPC between 1999 and 2019 were obtained from the Korea Central Cancer Registry. CS was analyzed across strata including histology groups (ductal adenocarcinoma excluding cystic or mucinous [group I, PDAC] and ductal adenocarcinoma specified as mucinous or cystic adenocarcinoma [group II]), and age.

RESULTS

For PDAC, the overall 5-year relative survival (RS) rate at diagnosis, 3-year CS of 2-year survivors, and 5-year CS of 5-year survivors were 8.5%, 50.1%, and 77.6%, respectively. Overall conditional probabilities of death were 85.2% (≥ 80 years), 73.5% (70-79 years), and 62.0% (60-69 years) in year 1 after diagnosis. Among patients with localized or regional stage who underwent surgery, conditional probabilities of death of ≥ 80, 70-79, and 60-69 years were 37.7%, 32.5%, and 22.6% in the first year, and 26.6%, 27.2%, and 26.0% in year 2 after diagnosis.

CONCLUSIONS

Half of patients with EPC who survived for 2 years survived for an additional 3 years. However, 5-year PDAC survivors require follow-up as more than 20% do not survive for a further 5 years. Elderly patients should not be excluded from active treatment for localized or regional-stage PDAC, as the CS of elderly patients who are fit enough to undergo surgery is not inferior to that of younger patients.

Racial disparities in conditional survival of patients with bladder cancer: a population-based study

BACKGROUND

Traditional estimates can only provide static predictions of cancer outcomes and cannot assess the evolving effect of race on patient survival. This study aims to reveal the dynamic survival of patients with bladder cancer and to explore the evolving effect of race on patient prognosis.

METHODS

Using data from the Surveillance, Epidemiology, and End Results (SEER) registry, 99,590 white, 6,036 African American, and 4,685 Asian/Pacific Islander (API) patients with bladder cancer were identified. Conditional cancer-specific survival (CSS) rates, which could reflect the dynamic survival prediction of cancer patients, represented the primary outcomes, and were estimated by the Kaplan-Meier algorithm. The evolving effect of race on patient survival was evaluated by multivariable Cox regression in combination with conditional survival (CS) estimates.

RESULTS

The 5-year CSS for African American patients who had survived 1, 2, 3, 4, or 5 years after definitive therapy improved from the baseline calculation by + 5.8 (84.4%), + 9.5 (87.4%), + 12.8 (90.0%), + 14.4 (91.3%), and + 14.7% (91.5%), respectively. The increasing trend also held for overall white and API patients, and for all patient subsets when CS was calculated according to different levels of sex, age, and disease stage. African Americans, despite having the worst survival at baseline, could have CSS comparable to their white and API counterparts after 4 years of survivorship. In addition, the risk of death for African Americans tended to decrease with increasing survival, and the risk was no longer significantly different from that of whites after 4 years of survival.

CONCLUSIONS

While having the worst initial predicted outcomes, African Americans may eventually achieve comparable survival to white and API patients given several years of survivorship. As patient survival increases, African American race may lose its role as an indicator of poorer prognosis.

Conditional survival analysis and real-time prognosis prediction for cervical cancer patients below the age of 65 years

Background

Survival prediction for cervical cancer is usually based on its stage at diagnosis or a multivariate nomogram. However, few studies cared whether long-term survival improved after they survived for several years. Meanwhile, traditional survival analysis could not calculate this dynamic outcome. We aimed to assess the improvement of survival over time using conditional survival (CS) analysis and developed a novel conditional survival nomogram (CS-nomogram) to provide individualized and real-time prognostic information.

Methods

Cervical cancer patients were collected from the Surveillance, Epidemiology, and End Results (SEER) database. The Kaplan-Meier method estimated cancer-specific survival (CSS) and calculated the conditional CSS (C-CSS) at year y+x after giving x years of survival based on the formula C-CSS(y|x) =CSS(y+x)/CSS(x). y indicated the number of years of further survival under the condition that the patient was determined to have survived for x years. The study identified predictors by the least absolute shrinkage and selection operator (LASSO) regression and used multivariate Cox regression to demonstrate these predictors' effect on CSS and to develop a nomogram. Finally, the CSS possibilities predicted by the nomogram were brought into the C-CSS formula to create the CS-nomogram.

Results

A total of 18,511 patients aged <65 years with cervical cancer from 2004 to 2019 were included in this study. CS analysis revealed that the 15-year CSS increased year by year from the initial 72.6% to 77.8%, 84.5%, 88.8%, 91.5%, 93.5%, 94.8%, 95.7%, 96.4%, 97.3%, 98.0%, 98.5%, 99.1%, and 99.4% (after surviving for 1-13 years, respectively), and found that when survival exceeded 5-6 years, the risk of death from cervical cancer would be less than 5% in 10-15 years. The CS-nomogram constructed using tumor size, lymph node status, distant metastasis status, and histological grade showed strong predictive performance with a concordance index (C-index) of 0.805 and a stable area under the curve (AUC) between 0.795 and 0.816 over 15 years.

Conclusions

CS analysis in this study revealed the gradual improvement of CSS over time in long-term survived cervical cancer patients. We applied CS to the nomogram and developed a CS-nomogram successfully predicting individualized and real-time prognosis.

Causes of death and conditional survival estimates of long-term lung cancer survivors

Introduction

Lung cancer ranks the leading cause of cancer-related death worldwide. This retrospective cohort study was designed to determine time-dependent death hazards of diverse causes and conditional survival of lung cancer.

Methods

We collected 816,436 lung cancer cases during 2000-2015 in the SEER database, after exclusion, 612,100 cases were enrolled for data analyses. Cancer-specific survival, overall survival and dynamic death hazard were assessed in this study. Additionally, based on the FDA approval time of Nivolumab in 2015, we evaluated the effect of immunotherapy on metastatic patients’ survival by comparing cases in 2016-2018 (immunotherapy era, n=7135) and those in 2013-2016 (non-immunotherapy era, n=42061).

Results

Of the 612,100 patients, 285,705 were women, the mean (SD) age was 68.3 (11.0) years old. 252,558 patients were characterized as lung adenocarcinoma, 133,302 cases were lung squamous cell carcinoma, and only 78,700 cases were small cell lung carcinomas. TNM stage was I in 140,518 cases, II in 38,225 cases, III in 159,095 cases, and IV in 274,262 patients. 164,394 cases underwent surgical intervention. The 5-y overall survival and cancer-specific survival were 54.2% and 73.8%, respectively. The 5-y conditional survival rate of cancer-specific survival is improved in a time-dependent pattern, while conditional overall survival tends to be steady after 5-y follow-up. Except from age, hazard disparities of other risk factors (such as stage and surgery) diminished over time according to the conditional survival curves. After 8 years since diagnosis, mortality hazard from other causes became higher than that from lung cancer. This critical time point was earlier in elder patients while was postponed in patients with advanced stages. Moreover, both cancer-specific survival and overall survival of metastatic patients in immunotherapy era were significantly better than those in non-immunotherapy era (P<0.001), indicating that immunotherapeutic intervention indeed bring remarkable benefits to advanced lung cancer patients.

Conclusions

Our findings expand on previous studies by demonstrating that non-lung-cancer related death risk becomes more and more predominant over the course of follow-up, and we establish a personalized web-based calculator to determine this critical time point for long-term survivors. We also confirmed the survival benefit of advanced lung cancer patients in immunotherapy era.

Conditional survival of uveal melanoma using The Cancer Genome Atlas (TCGA) classification (Simplified Version) in 1001 cases

PURPOSE

To understand conditional prognostic value of the Cancer Genome Atlas (TCGA) for uveal melanoma metastasis based on event-free survival at 1, 2, 3, 4, and 5 years.

METHODS

A retrospective study of eyes with uveal melanoma categorized according to TCGA and studied for nonconditional and conditional risks for metastasis at 5 and 10 years.

RESULTS

Of 1001 eyes with uveal melanoma, the nonconditional (standard, at presentation) 5-year/10-year metastatic rate was 18%/25%. The conditional 5-year/10-year metastatic rate (for those without metastasis at 2 years) revealed 10%/18% and the conditional 10-year metastatic rate (for those without metastasis at 5 years) revealed 9%. The TCGA categories included Group A (n = 486, 49%), B (n = 141, 14%), C (n = 260, 26%), and D (n = 114, 11%). The non-conditional 5-year/10-year metastatic rate revealed Group A (4%/6%), Group B (12%/20%), Group C (23%/49%), and Group D (60%/68%). The conditional 5-year/10-year metastatic rate (for those without metastasis at 2 years) revealed Group A (2%/5%), Group B (8%/18%), Group C (21%/40%), and Group D (38%/50%). The conditional 10-year metastatic rate (for those without metastasis at 5 years) revealed Group A (2%), Group B (10%), Group C (33%), and Group D (20%). The peak incidence of metastasis for Groups A and B occurred during years 5-6, C during years 4-6, and D during years 1-2.

CONCLUSION

Survival outcomes for uveal melanoma as non-conditional (at presentation) and conditional (event-free survival during follow-up) reveal reduction in metastatic rate over time. For those with 5-year metastasis-free survival, the 10-year conditional risk for metastasis was 9%.

Conditional survival of metastatic clear cell renal cell carcinoma: How prognosis evolves after cytoreductive surgery of primary tumor

Introduction

Cytoreductive surgery is one of the recommended treatments for metastatic renal cell carcinoma, while the prognostic information of these patients treated with cytoreductive surgery is limited. In this study, we aimed to investigate the survival profiles based on conditional survival (CS) estimates in metastatic clear cell renal cell carcinoma (mccRCC) patients treated with cytoreductive surgery of primary tumor.

Methods and materials

We identified and extracted mccRCC patients from the Surveillance, Epidemiology, and End Results database. We used Kaplan–Meier method to perform CS analyses. A multivariate Cox regression model was applied to explore the changes of well‐known prognostic factors.

Results

Conditional overall survival (COS) and conditional cancer‐specific survival (CCSS) improved increasingly at all periods of survivorships compared to survival estimates at baseline in overall population of mccRCC. The 36‐month COS improved by 3.3%–6.4% given per 12 additional months of survivorships and the CCSS improved significantly from 45.1% (95% CI 42.8–47.3) at 12 months to 67.1% (95% CI 62.0–71.7) at 60 months. Much more survival gain was observed in patients with advanced disease. Furthermore, the prognostic significance of age and pathological factors diminished and even disappeared in a long‐term survivorship.

Conclusions

Conditional overall survival and CCSS improved with time dynamically in mccRCC patients treated with cytoreductive surgery of primary tumor. Patients with advanced disease achieved significant survival gain and even could harvest a better prognosis given that the time of survivorship exceeds a certain period. Our findings could provide valuable and practical data for patient counseling and surveillance strategy making.

Conditional Survival, Cause-Specific Mortality, and Risk Factors of Late Mortality After Allogeneic Hematopoietic Cell Transplantation

BACKGROUND

Long-term mortality after hematopoietic cell transplantation (HCT) is conventionally calculated from the time of HCT, ignoring temporal changes in survivors' mortality risks. Conditional survival rates, accounting for time already survived, are relevant for optimal delivery of survivorship care but have not been widely quantified. We estimated conditional survival by elapsed survival time in allogeneic HCT patients and examined cause-specific mortality.

METHODS

We calculated conditional survival rates and standardized mortality ratio for overall and cause-specific mortality in 4485 patients who underwent HCT for malignant hematologic diseases at a large transplant center during 1976-2014. Statistical tests were two-sided.

RESULTS

The 5-year survival rate from HCT was 48.6%. After surviving 1, 2, 5, 10, and 15 years, the subsequent 5-year survival rates were 71.2%, 78.7%, 87.4%, 93.5%, and 86.2%, respectively. The standardized mortality ratio was 30.3 (95% confidence interval [CI] = 29.2 to 35.5). Although the standardized mortality ratio declined in longer surviving patients, it was still elevated by 3.6-fold in survivors of 15 years or more (95% CI = 3.0 to 4.1). Primary disease accounted for 50% of deaths in the overall cohort and only 10% in 15-year survivors; the leading causes of nondisease-related mortality were subsequent malignancy (26.1%) and cardiopulmonary diseases (20.2%). We also identified the risk factors for nondisease-related mortality in 1- and 5-year survivors.

CONCLUSION

Survival probability improves the longer patients survive after HCT. However, HCT recipients surviving 15 years or more remain at elevated mortality risk, largely because of health conditions other than their primary disease. Our study findings help inform preventive and interventional strategies to improve long-term outcomes after allogeneic HCT.

New Model for Estimation of the Age at Onset in Spinocerebellar Ataxia Type 3

OBJECTIVES

The aim of this study was to develop an appropriate parametric survival model to predict patient's age at onset (AAO) for spinocerebellar ataxia type 3/Machado-Joseph disease (SCA3/MJD) populations from mainland China.

METHODS

We compared the efficiency and performance of 6 parametric survival analysis methods (exponential, weibull, log-gaussian, gaussian, log-logistic, and logistic) based on cytosine-adenine-guanine (CAG) repeat length at ATXN3 to predict the probability of AAO in the largest cohort of patients with SCA3/MJD. A set of evaluation criteria, including -2 log-likelihood statistic, Akaike information criterion (AIC), bayesian information criterion (BIC), Nagelkerke R-squared (Nagelkerke R^2), and Cox-Snell residual plot, were used to identify the best model.

RESULTS

Among these 6 parametric survival models, the logistic model had the lowest -2 log-likelihood (6,560.12), AIC (6,566.12), and BIC (6,566.14) and the highest value of Nagelkerke R^2 (0.54), with the closest graph to the bisector Cox-Snell residual graph. Therefore, the logistic survival model was the best fit to the studied data. Using the optimal logistic survival model, we indicated the age-specific probability distribution of AAO according to the CAG repeat size and current age.

CONCLUSIONS

We first demonstrated that the logistic survival model provided the best fit for AAO prediction in patients with SCA3/MJD from mainland China. This optimal model can be valuable in clinical and research. However, the rigorous clinical testing and practice of other independent cohorts are needed for its clinical application. A unified model across multiethnic cohorts is worth further exploration by identifying regional differences and significant modifiers in AAO determination.

Development and validation of the trans-omics model for pancreatic adenocarcinoma

Aim: To develop a trans-omics-based molecular clinicopathological algorithm for predicting pancreatic adenocarcinoma prognosis, we performed a comprehensive analysis of the expression levels of mRNA, DNA methylation and DNA copy number in The Cancer Genome Atlas dataset. Materials & methods: Based on the least absolute shrinkage and selection operator method - COX regression analysis, a trans-omics-based classifier was established to predict overall survival. Nomogram was constructed by combining the classifier band clinical pathological characterization. Results: Based on trans-omics, we developed a 10-gene-based classifier and a molecular-clinicopathologic nomogram for predicting overall survival with satisfactory accuracy. Conclusion: Trans-omics-based classifier and molecule-clinicopathological nomogram based on the classifier can accurately predict the prognosis of pancreatic adenocarcinoma patients.

Redefining Conditional Overall and Disease-Free Survival After Curative Resection for Intrahepatic Cholangiocarcinoma: a Multi-institutional, International Study of 1221 patients

OBJECTIVES

To assess conditional survival (CS) according to recurrence status, as well as conditional disease-free survival (cDFS) among patients with intrahepatic cholangiocarcinoma (ICC).

METHODS

CS and cDFS were evaluated among ICC patients who underwent curative-intent resection for ICC by using a multi-institutional database. Five-year CS (CS5) at "x" years was calculated separately for patients who did and did not experience recurrence. The cDFS3 at "x" years was defined as the chance to be disease-free for an additional 3 years after not having experienced a recurrence for "x" years postoperatively.

RESULTS

Among 1221 patients, median OS was 36.8 months. While estimated actuarial OS decreased over time, CS5 increased as patients survived over longer periods of time and reached 93.9% at 4 years among 139 patients who did not experience a recurrence. Among the 725 (59.4%) patients who did experience a tumor recurrence, CS5 decreased to 17.7% the first postoperative year; however, CS5 subsequently increased to 79.7% for 81 patients who had survived 4 years after surgery. While actuarial DFS decreased from 54.6% at 1 year to 28.2% at 5 years, estimated cDFS3 following liver resection increased over time. Of note, patients with known risk factors for recurrence had even more marked improvements in cDFS3 over subsequent years versus patients without risk factors for recurrence.

CONCLUSION

CS and cDFS changed over time according to the presence of disease-specific risk factors, as well as the presence of recurrence.

Conditional survival after surgery for patients with penile cancer

BACKGROUND

Penile cancer represents a rare pathology whose natural history of treatment is poorly understood.

OBJECTIVE

To illustrate the dynamic survival profiles in surgically treated patients with squamous cell carcinoma of the penis (SCCP) using the conditional survival (CS) estimates.

MATERIALS AND METHODS

Patients with non-metastatic SCCP were identified from the Surveillance, Epidemiology, and End Results (SEER) database. Conditional 3-yr overall survival (OS) rate and 3-yr cancer-specific survival (CSS) rate represented the primary outcomes of interest and were calculated using the Kaplan-Meier method. The multivariable Cox regression model was employed to calculate proportional hazard ratios for the prediction of mortality.

RESULTS

A total of 1887 SCCP patients who had undergone surgeries were identified. Given a 1-, 2-, 3-, 4-, and 5-yr survivorship, the 3-yr OS rates were, respectively, improved by + 9.8 (72.6%), +18.2 (78.1%), +23.4 (81.6%), +27.8 (84.5%), and + 26.6% (83.7%) from those calculated at baseline (time zero). As compared with the baseline calculations, patients who had survived 1, 2, 3, 4, or 5 yr after surgery could, respectively, harvest a + 7.8 (84.7%), +14.8 (90.2%), +19.5 (93.9%), +22.1 (96.0%), and + 22.4% (96.2%) improvement in 3-yr CSS. Patients with the most aggressive disease at baseline ultimately benefited the most from event-free survivorship. Multivariable Cox regression analyses showed that the impact of adverse pathological parameters (G2-3, ≥ pT2, pN+) on OS and CSS mostly showed a decreasing trend over time and some could disappear after a minimum of 1-yr survivorship.

DISCUSSION AND CONCLUSION

The survival probability of SCCP patients increases with post-operative survival. Patients with aggressive disease at baseline ultimately benefit the most from event-free survivorship and may expect a better prognosis once they survive the critical few years after surgery. The recorded observations have crucial implications regarding patient counseling and follow-up.

Dynamic prediction of cancer-specific survival for primary hypopharyngeal squamous cell carcinoma

OBJECTIVES

This study investigated a large cohort of patients to construct a predictive nomogram and a web-based survival rate calculator for dynamically predicting the cancer-specific survival of patients with primary hypopharyngeal squamous cell carcinoma (HSCC).

METHODS

Patients (n = 2007) initially diagnosed with primary HSCC from 2004 to 2015 were extracted from the Surveillance, Epidemiology, and End Results (SEER) database. All patients were randomly divided into the training and validation cohorts (1:1). The Lasso Cox regression model was applied to identify independent risk factors of cancer-specific survival for a predictive nomogram and a web-based calculator. The model was evaluated by concordance index, calibration, and decision curve analysis.

RESULTS

Cancer-specific survival rates decreased with time, while 3-year conditional survival increased. Cancer-specific deaths evolved from relatively high within the first 3 years to low thereafter. Age, race, T stage, N stage, M stage, surgery, radiotherapy, chemotherapy, and marital status were identified as independent risk factors. We constructed a predictive nomogram for survival and a web-based calculator ( https://linzhongyang.shinyapps.io/Hypopharyngeal/ ). Additionally, a prognostic risk stratification was developed according to nomogram total points.

CONCLUSIONS

Patients with primary HSCC were found at a high risk of cancer-specific death during the first 3 years, indicating that additional effective follow-up strategies should be implemented over the period. This is the first study to construct a predictive nomogram and a web-based calculator for all patients with HSCC.

Dynamic evaluation of conditional survival in patients with oral squamous cell carcinoma after surgical resection: A large-scale prospective study

OBJECTIVE

To dynamically estimate conditional survival (CS) probabilities for patients with oral squamous cell carcinoma (OSCC) after surgical resection.

METHOD

A large-scale prospective study was performed involving 1147 eligible OSCC patients from December 2002 to June 2018. Follow-up was completed on January 8, 2019. Cox proportional hazards models were utilized to assess prognostic factors related to overall survival (OS). Three-year CS (CS₃) of patients who had already survived x years was calculated as the formula CS₃ = OS_(x+3)/OS(x).

RESULTS

CS₃ estimates at the time of 0, 1, 3, 5-year survival demonstrated a tendency increase over time, and improved from 78.47% to 82.25%, while the postoperative actuarial OS decreased from 78.47% at 3 years to 57.12% at 8 years. Moreover, the differences between CS₃ and actuarial OS were more obvious among patients with unfavorable tumor characteristics. Disparities in CS₃ across all subgroups of tumor features illustrated more prominent at baseline (d range: 0.24 to 0.40), while the gaps would narrow if those patients have already survived 5 years (d range: -0.01 to 0.18).

CONCLUSION

Our findings suggest that survival profiles of OSCC patients evolve and increase over time following resection, especially for those with unfavorable tumor features at initial diagnosis. CS estimates may provide more accurate prediction and guide surveillance schedules.