Search

The aim of this study was to explore the high-risk factors for recurrence in patients with locally advanced esophageal squamous cell carcinoma (ESCC) undergoing definitive chemoradiotherapy or radiotherapy (dCRT or dRT). Conditional survival (CS) was used to evaluate the dynamic survival and recurrence risk of patients after treatment, and individualized monitoring strategies were developed for patients. Logistic regression analysis was performed to determine independent recurrence risk factors. Calibration curves and receiver operating characteristic (ROC) curve were used to evaluate nomogram models. Kaplan–Meier curves were used to compare survival rates in different groups and to calculate CS rate. A total of 677 patients were included. Multivariate logistic analyses demonstrated that chemotherapy cycles, tumor length, body mass index (BMI), platelet-lymphocyte ratio (PLR), and lymphocyte-monocyte ratio (LMR) were independent recurrence risk factors (p < 0.05). Subsequently, we constructed nomogram models to predict recurrence and risk stratification. Kaplan–Meier curves showed that conditional locoregional recurrence-free survival and distant metastasis-free survival of patients in different risk groups and clinical stages progressively increased with survival time, whereas local recurrence and distant metastasis annual recurrence rates decreased yearly with increasing survival time. Finally, we developed an individualized follow-up strategy based on CS at different frequencies. Individualized follow-up strategies developed on the basis of CS can better monitor the changes in patients' conditions and contribute to timely salvage treatment and rational allocation of healthcare resources. [ABSTRACT FROM AUTHOR]

Objective: Little is known about the changing risk profile of death and conditional survival in patients with operable thyroid cancer. This study aimed to investigate the annual hazard rate of cancer death, actuarial disease-specific survival (DSS), and conditional DSS in patients with thyroid cancer and explore the effects of tumor differentiation. Methods: Patients diagnosed with thyroid cancer (N = 132,354) between 2004 and 2019 were identified from the Surveillance, Epidemiology, and End Results database. The hazard function was used to estimate the annual hazard rate of death. The Kaplan-Meier method and log-rank test were used for the calculation and between-group comparison of actuarial DSS, respectively. The life table was used to estimate the conditional DSS. Results: A total of 1896 (1.4%) patients died due to thyroid cancer during the follow-up period. Patients with ATC (68.9%, 313/454) were more likely to die than those with PDTC (19.4%, 171/883) or DTC (1.1%, 1412/131017). For the entire cohort, patients with DTC and PDTC had excellent and relatively stable one-year conditional survival, respectively; patients with ATC had the worst one-year conditional survival, but they achieved the greatest improvements. The worst one-year conditional survival and the most obvious improvement were seen in patients with ATC regardless of any SEER Summary Stage. Conclusion: Prognosis improved over time in a tumor differentiation-dependent manner in patients with operable thyroid cancer after diagnosis. This information provides more precise dynamic evaluations of the long-term prognosis of thyroid cancer survivors and paramount clinical implications for individualized treatment and surveillance. [ABSTRACT FROM AUTHOR]

PurposeMethodsResultsConclusionTo determine the impact of uveal melanoma thickness on patient survival from the date of presentation and at specific time intervals following metastasis-free survival.In this retrospective cohort study, we evaluated data from 8034 consecutive uveal melanoma patients diagnosed at a tertiary care ocular oncology center between May 1972 and August 2007. The patients were categorized on the basis of tumor thickness (per each 1-mm increment) and evaluated for non-conditional survival (from date of presentation) and conditional survival (with 3-years, 5-years, and 10-years of metastasis-free survival) on the cumulative incidence of melanoma-related metastasis at 5-, 10-, 15-, 20-, 25- and 30-years.For the entire cohort, Non-conditional incidence of metastasis at 5-, 10-, 15-, and 30-years was 8%, 11%, 12%, and 12%. Conditional cumulative incidence of metastasis with 5-year and 10-year metastasis-free survival revealed 30-year incidence of metastasis at 10% and 8%, respectively. The multivariate Cox regression analysis showed that each 1-mm increase in tumor thickness was associated with a significant (p < .05) increase in the risk of metastasis [HR: 1.08 (95% CI: 1.05–1.11) for non-conditional survival, HR: 1.07 (95% CI: 1.03–1.11) for 3-year metastasis-free survival, HR: 1.09 (95% CI: 1.03–1.15) for 5-year metastasis-free survival, and HR: 1.17 (95% CI: 1.05–1.30) for 10-year metastasis-free survival].In this study, we emphasize that increasing the thickness of uveal melanoma at presentation demonstrates a poorer ultimate prognosis. However, those with longer metastasis-free intervals were found to have a lower risk of ultimate metastatic disease, highlighting the importance of conditional and non-conditional survival. [ABSTRACT FROM AUTHOR]

Abstract Background Traditional survival analysis is frequently used to assess the prognosis of ependymomas (EPNs); however, it may not provide additional survival insights for patients who have survived for several years. Thus, the conditional survival (CS) pattern of this disease is yet to be further investigated. This study aimed to evaluate the improvement of survival over time using CS analysis and develop a CS-based nomogram model for real-time dynamic survival estimation for EPN patients. Methods Data on patients with EPN were collected from the Surveillance, Epidemiology, and End Results (SEER) database. In order to construct and validate the model effectively, the selected patients were randomly divided at 7:3 ratio. CS is defined as the probability of surviving for a specified time period (y years) after initial diagnosis, given that the patient has survived x years. The CS pattern of EPN patients were explored. Then, the least absolute shrinkage and selection operator (LASSO) regression method with tenfold cross-validation was employed to identify prognostic predictors. Multivariate Cox regression was employed to develop a CS-based nomogram model, and we used this model to quantify EPN patient risk. Finally, the performance of the prediction model was also evaluated and verified. Results In total, 1829 patients diagnosed with EPN were included in the study, with 1280 and 549 patients in the training and validation cohorts, respectively. The CS analysis demonstrated that patients' OS saw gradual improvements over time. With each additional year of survival post-diagnosis, the 10-year survival rate of EPN patients saw an increase, updating from 74% initially to 79%, 82%, 85%, 87%, 89%, 91%, 93%, 96%, and 98% (after surviving for 1–9 years, respectively). The LASSO regression model, which implements tenfold cross-validation, identified 7 significant predictors (age, tumor grade, tumor site, tumor extension, tumor size, surgery and radiotherapy) to develop a CS-based nomogram model. And further risk stratification was conducted based on nomogram model for these patients. Furthermore, this survival prediction model was successfully validated. Conclusion This study described the CS pattern of EPN patients and highlighted the gradual improvement of survival observed over time for long-term survivors. We also developed the first novel CS-nomogram model that enabled individualized and real-time prognosis prediction. But patients must be counselled that individual circumstances may not always accurately reflect the findings of the nomogram.

Summary During a fatal disease, patients often request updated information on their prognosis. After patients have already survived a certain time, conditional survival captures their future survival probability. We investigated conditional overall and failure‐free survival in 473 younger mantle cell lymphoma (MCL) patients from a randomized phase III trial comparing immunochemotherapies R‐CHOP and alternating R‐CHOP/R‐DHAP before autologous transplantation. Using conditional Kaplan–Meier method and Cox regression, we estimated subsequent survival of patients who had survived 1–8 years, considering MIPI, Ki‐67, and treatment failure status. Starting at a lower level, R‐CHOP patients only showed increasing subsequent survival as they survived longer (5‐year conditional survival: 72% and 81% after surviving 1 and 7 years), while R‐CHOP/R‐DHAP patients had stable future survival over time (77% and 78%). The prognostic value of MIPI diminished after 3 years in R‐CHOP patients but remained unchanged after R‐CHOP/R‐DHAP. Patients with treatment failure had markedly inferior survival compared with those in ongoing remission, regardless of the time survived. The longer patients remained in remission, the longer they would stay free of treatment failures. Our results enable personalized counselling for younger MCL patients by offering dynamic prognosis and underscore the importance of highly effective first‐line treatment to improve survival. [ABSTRACT FROM AUTHOR]

Background: Locally advanced rectal cancer (LARC) is one of the most common malignant tumors worldwide, and its incidence is increasing year by year. Despite multimodal treatment, the recurrence rate of LARC patients remains high, about 20%–50%. However, the follow‐up strategy according to tumor stage has certain limitations. There is no consensus on the optimal frequency and duration of follow‐up. This study aims to comprehensively analyze the high‐risk factors for recurrence in LARC from clinical characteristics, nutritional indicators, and imaging indexes. It intends to utilize conditional survival (CS) evaluation to assess dynamic survival and recurrence risks after comprehensive treatment of LARC and to develop individualized follow‐up strategies. Methods: Logistic regression was utilized to analyze the independent recurrence factors in LARC patients. Calibration curve, decision curve, and ROC curve were employed to evaluate the model's efficacy. Kaplan–Meier curve was used to calculate CS rate and compare survival differences among different risk groups. Results: A total of 561 patients were analyzed in our study. Our multivariable logistic regression analysis revealed that the prognostic nutritional index (PNI), extramural vascular invasion (EMVI), vascular tumor thrombus, perineural invasion, and tumor size were independent factors for recurrence. Subsequently, a nomogram model was constructed and risk stratification was performed. Calibration curves and decision curves demonstrated that the model exhibited good clinical efficacy. The area under the ROC curve for the model was 0.763, indicating good sensitivity and specificity. Kaplan–Meier curves showed significant differences in survival among different risk groups. Furthermore, we observed that the CS without local recurrence and distant metastasis increased each year, while the cumulative recurrence risk decreased annually with prolonged survival time. Tailored follow‐up intensities were developed for different risk groups and clinical stages based on the cumulative recurrence risk. Conclusion: The personalized follow‐up strategy based on risk stratification can optimize resource allocation, early detection of recurrence or metastasis, and ultimately enhance the overall care and prognosis of LARC patients. [ABSTRACT FROM AUTHOR]

The aim was to assess conditional survival for colon mucinous adenocarcinoma (MAC) patients, and to construct nomograms to predict conditional survival probability. Survival analysis was done using conditional survival, which was defined as the probability of surviving additional y years for patients who have survived for x years. The mathematical definition was express as: CS (y|x) = S (x + y)/S (x). Cox regression analyses were used to identify prognostic factors. A nomogram is constructed to predict conditional disease-free survival (DFS) and overall survival (OS) probability according to years that already survive. A total of 179 colon MAC patients were included. The 5-year DFS was 67% after surgery, and the 5-year survival probability of patients, who already survived 1, 2, 3, and 4 years were 75%, 87%, 95%, and 98%, respectively. The 5-year OS was 73% after surgery and increased to 76%, 82%, 88%, and 92% at 1, 2, 3, and 4 years, respectively. Subgroup analyses demonstrated the superiority of conditional survival was more pronounced in advanced stages than in stage I. And pT stage, pN stage, and lymphovascular invasion were significantly associated with DFS and OS. Conditional survival nomograms were constructed to predict the 5-year conditional DFS and OS probability given survival for 1, 2, 3, 4 years after surgery. Conditional survival can provide dynamic survival probability according to years that already survive, especially for patients with advanced stages. Taking into account the years already survived accounted for, novel nomograms contributed to effectively predicting conditional survival. [ABSTRACT FROM AUTHOR]

Background: The real-time prognostic data of patients with poorly differentiated thyroid carcinoma (PDTC) after surviving for several years was unclear. This study aimed to employ a novel method to dynamically estimate survival for PDTC patients. Methods: A total of 913 patients diagnosed with PDTC between 2014 and 2015 from the Surveillance, Epidemiology, and End Results (SEER) database, was recruited in our study. Kaplan--Meier method was used to estimate the overall survival (OS). The conditional survival (CS) outcomes of PDTC were analyzed and CS rates were calculated using the formula CS(y/x) = OS(y+x)/OS(x), whereby CS(y/x) denotes the probability of a patient enduring an additional y years subsequent to surviving x years following the diagnosis of PDTC. The least absolute shrinkage and selection operator (LASSO) regression was employed to identify prognostic predicters and multivariate Cox regression was utilized to develop a CS-nomogram. Finally, the performance of this model was evaluated and validated. Results: Kaplan--Meier survival analysis unveiled patient outcomes demonstrating an OS rate of 83%, 75%, and 60% respectively at the end of 3, 5, and 10 years. The novel CS analysis highlighted a progressive enhancement in survival over time, with the 10-year cumulative survival rate progressively augmenting from its initiation of 60% to 66%, 69%, 73%, 77%, 81%, 83%, 88%, 93%, and finally 97% (after surviving for 1-9 years, respectively) each year. And then 11 (11/15) predictors including age at diagnosis, sex, histology type, SEER stage, T stage, N stage, M stage, tumor size, coexistence with other malignancy, radiotherapy and marital status, were selected by LASSO analysis under the condition of lambda.min. Multivariate Cox regression analysis further highlighted the significant impact of all these predictors on the OS of PDTC and we successfully established and validated a novel CS-nomogram for real-time and dynamic survival prediction. Conclusions: This was the first study to analyze the CS pattern and demonstrate a gradual improvement in CS over time in long-term PDTC survivors. We then successfully developed and validated a novel CS-nomogram for individualized, dynamic, and real-time survival forecasting, empowering clinicians to adapt and refine the patient-tailored treatment strategy promptly with consideration of evolving risks. [ABSTRACT FROM AUTHOR]

Background: Traditional survival analysis is frequently used to assess the prognosis of ependymomas (EPNs); however, it may not provide additional survival insights for patients who have survived for several years. Thus, the conditional survival (CS) pattern of this disease is yet to be further investigated. This study aimed to evaluate the improvement of survival over time using CS analysis and develop a CS-based nomogram model for real-time dynamic survival estimation for EPN patients. Methods: Data on patients with EPN were collected from the Surveillance, Epidemiology, and End Results (SEER) database. In order to construct and validate the model effectively, the selected patients were randomly divided at 7:3 ratio. CS is defined as the probability of surviving for a specified time period (y years) after initial diagnosis, given that the patient has survived x years. The CS pattern of EPN patients were explored. Then, the least absolute shrinkage and selection operator (LASSO) regression method with tenfold cross-validation was employed to identify prognostic predictors. Multivariate Cox regression was employed to develop a CS-based nomogram model, and we used this model to quantify EPN patient risk. Finally, the performance of the prediction model was also evaluated and verified. Results: In total, 1829 patients diagnosed with EPN were included in the study, with 1280 and 549 patients in the training and validation cohorts, respectively. The CS analysis demonstrated that patients' OS saw gradual improvements over time. With each additional year of survival post-diagnosis, the 10-year survival rate of EPN patients saw an increase, updating from 74% initially to 79%, 82%, 85%, 87%, 89%, 91%, 93%, 96%, and 98% (after surviving for 1–9 years, respectively). The LASSO regression model, which implements tenfold cross-validation, identified 7 significant predictors (age, tumor grade, tumor site, tumor extension, tumor size, surgery and radiotherapy) to develop a CS-based nomogram model. And further risk stratification was conducted based on nomogram model for these patients. Furthermore, this survival prediction model was successfully validated. Conclusion: This study described the CS pattern of EPN patients and highlighted the gradual improvement of survival observed over time for long-term survivors. We also developed the first novel CS-nomogram model that enabled individualized and real-time prognosis prediction. But patients must be counselled that individual circumstances may not always accurately reflect the findings of the nomogram. [ABSTRACT FROM AUTHOR]

OBJECTIVES Despite excellent 5-year survival, there are limited data on the long-term prognostic characteristics of clinical stage IA part-solid lung adenocarcinoma. The objective was to elucidate the dynamics of prognostic characteristics through conditional survival analysis. METHODS Consecutive patients who underwent complete resection for clinical stage IA part-solid lung adenocarcinoma between 2011 and 2015 were retrospectively reviewed. Conditional survival is defined as the probability of surviving further y years, conditional on the patient has already survived x years. The conditional recurrence-free survival (CRFS) and conditional overall survival (COS) were analysed to evaluate prognosis over time, with conditional Cox regression analysis performed to identify time-dependent prognostic factors. RESULTS A total of 1539 patients were included with a median follow-up duration of 98.4 months, and 80 (5.2%) patients experienced recurrence. Among them, 20 (1.3%) recurrence cases occurred after 5 years of follow-up with 100% intrathoracic recurrence. The 5-year CRFS increased from 95.8% to 97.4%, while the 5-year COS maintained stable. Multivariable Cox analysis revealed that histologic subtype was always an independent prognostic factor for CRFS even after 5 years of follow-up, while the independent prognostic value of consolidation-to-tumour ratio, visceral pleural invasion and lymph node metastasis was observed only within 5 years. Besides, age, pathologic size and lymph node metastasis maintained independent predictive value for COS during long-term follow-up, while consolidation-to-tumour ratio was predictive for COS only within 5 years of follow-up. CONCLUSIONS The independent prognostic factors for clinical stage IA part-solid lung adenocarcinoma changed over time, along with gradually increasing 5-year CRFS and stable 5-year COS. [ABSTRACT FROM AUTHOR]

BackgroundConditional survival (CS) analysis can estimate further survival probabilities based on the time already survived, providing dynamic updates for prognostic information. This study aimed to develop a CS-nomogram to promote individualized disease management for stage III non-small cell lung cancer (NSCLC).MethodsThis study included patients diagnosed with stage III NSCLC in the Surveillance, Epidemiology, and End Results database from 2010 to 2017 (N = 3,512). The CS was calculated as CS(y|x) = OS(y + x)/OS(x), where OS(y + x) and OS(x) were the overall survival (OS) in the year (y + x) and year x, respectively, calculated by the Kaplan–Meier method. We used the least absolute shrinkage and selection operator (LASSO) regression to identify predictors and developed the CS-nomogram based on these predictors and the CS formula.ResultsThe CS analysis provided real-time updates on survival, with 5-year OS improving dynamically from 14.4 to 29.9%, 47.9, 66.0, and 80.8% (after 1–4 years of survival). Six independent predictors (age, tumor size, N status, surgery, radiotherapy and chemotherapy) were identified for the development of the CS-nomogram and its web version (https://dynapp.shinyapps.io/NSCLC/). The model performed with an excellent concordance index (C-index) of 0.71 (95% CI: 0.70–0.72), and a median time-dependent AUC of 0.71–0.73 from 200 iterations 5-fold cross-validation.ConclusionThe study demonstrated the improvement in real-time OS over time in stage III NSCLC survivors and developed the novel CS-nomogram to provide patients with updated survival data. It provided novel insights into clinical decisions in follow-up and treatment for survivors, offering a convenient tool for optimize resource allocation.

ObjectiveLittle is known about the changing risk profile of death and conditional survival in patients with operable thyroid cancer. This study aimed to investigate the annual hazard rate of cancer death, actuarial disease-specific survival (DSS), and conditional DSS in patients with thyroid cancer and explore the effects of tumor differentiation.MethodsPatients diagnosed with thyroid cancer (N = 132,354) between 2004 and 2019 were identified from the Surveillance, Epidemiology, and End Results database. The hazard function was used to estimate the annual hazard rate of death. The Kaplan-Meier method and log-rank test were used for the calculation and between-group comparison of actuarial DSS, respectively. The life table was used to estimate the conditional DSS.ResultsA total of 1896 (1.4%) patients died due to thyroid cancer during the follow-up period. Patients with ATC (68.9%, 313/454) were more likely to die than those with PDTC (19.4%, 171/883) or DTC (1.1%, 1412/131017). For the entire cohort, patients with DTC and PDTC had excellent and relatively stable one-year conditional survival, respectively; patients with ATC had the worst one-year conditional survival, but they achieved the greatest improvements. The worst one-year conditional survival and the most obvious improvement were seen in patients with ATC regardless of any SEER Summary Stage.ConclusionPrognosis improved over time in a tumor differentiation-dependent manner in patients with operable thyroid cancer after diagnosis. This information provides more precise dynamic evaluations of the long-term prognosis of thyroid cancer survivors and paramount clinical implications for individualized treatment and surveillance.

Abstract Background To evaluate the clinical value of serum CEA levels and their implications on the diagnostic value of the conventional TNM staging system in the oldest-old patients with colorectal cancer (CRC). Methods The recruited subjects were colorectal cancer patients aged 85 and older. The cutoff value for normal CEA level is 5 ng/mL. Patients with elevated CEA levels were categorized as stage C1, and those with normal CEA levels as stage C0. A number of Cox proportional hazard regression models were established to evaluate the prognosis of different prognostic factors with hazard ratios (HRs) and 95% confidence intervals (CIs). The Kaplan–Meier method was utilized to display the disparate prognostic impact of multiple clinicopathological factors with the log-rank test. Results A total of 17,359 oldest-old patients diagnosed with CRC were recruited from the SEER database. The conditional survival of oldest-old patients with CRC was dismal with a 1-year conditional survival of only 11%, 18%, and 30% for patients surviving 1, 3, and 5 years, respectively. Patients with stage C1 exhibited a 48.5% increased risk of CRC-specific mortality compared with stage C0 (HR = 1.485, 95%CI = 1.393–1.583, using stage C0 patients as the reference, P

Background: To evaluate the clinical value of serum CEA levels and their implications on the diagnostic value of the conventional TNM staging system in the oldest-old patients with colorectal cancer (CRC). Methods: The recruited subjects were colorectal cancer patients aged 85 and older. The cutoff value for normal CEA level is 5 ng/mL. Patients with elevated CEA levels were categorized as stage C1, and those with normal CEA levels as stage C0. A number of Cox proportional hazard regression models were established to evaluate the prognosis of different prognostic factors with hazard ratios (HRs) and 95% confidence intervals (CIs). The Kaplan–Meier method was utilized to display the disparate prognostic impact of multiple clinicopathological factors with the log-rank test. Results: A total of 17,359 oldest-old patients diagnosed with CRC were recruited from the SEER database. The conditional survival of oldest-old patients with CRC was dismal with a 1-year conditional survival of only 11%, 18%, and 30% for patients surviving 1, 3, and 5 years, respectively. Patients with stage C1 exhibited a 48.5% increased risk of CRC-specific mortality compared with stage C0 (HR = 1.485, 95%CI = 1.393–1.583, using stage C0 patients as the reference, P < 0.001). All the stage C0 patients indicated lower HRs relative to the corresponding stage C1 patients. Conclusions: Dismal conditional survival of oldest-old patients with CRC should be given additional consideration. C stage influences the prognosis of oldest-old patients with CRC. [ABSTRACT FROM AUTHOR]

Background: The current survival prediction methodologies for primary bone lymphoma (PBL) of the spine are deficient. This study represents the inaugural utilization of conditional survival (CS) to assess the outcome of this disease. Moreover, our objective was to devise a CS-based nomogram for predicting overall survival (OS) in real-time for spinal PBL. Methods: Patients with PBL of the spine diagnosed between January 2000 and December 2015 were extracted from the Surveillance, Epidemiology, and End Results (SEER) database. The OS was determined through the Kaplan–Meier method. The CS characteristic of patients with spinal PBL was delineated, with the CS being estimated utilizing the formula: CS(α|β) = OS(α+β)/OS(β). CS(α|β) denotes the probability of additional α-year survivorship, assuming the patient has already survived β years after the time of observation. Three methods including univariate Cox regression, best subset regression (BSR) and the least absolute shrinkage and selection operator (LASSO) regression were used to identify predictors for CS-based nomogram construction. Results: Kaplan-Meier analysis was executed to determine the OS rate for these patients, revealing a survival rate of 68% and subsequently 63% at the 3-year and 5-year mark respectively. We then investigated the CS patterning exhibited by these patients and discovered the survival of PBL in the spine progressively improved with time. Meanwhile, through three different prognostic factor selection methods, we identified the best predicter subset including age, tumor histology, tumor stage, chemotherapy and marital status, for survival prediction model construction. Finally, we successfully established and validated a novel CS-based nomogram model for real-time and dynamic survival estimation. Moreover, we further designed a risk stratification system to facilitate the identification of high-risk patients. Conclusions: This is the first study to analyze the CS pattern of PBL of the spine. And we have also developed a CS-based nomogram that provide dynamic prognostic data in real-time, thereby aiding in the formulation of personalized treatment strategies in clinical practice. [ABSTRACT FROM AUTHOR]

Biomarkers in chronic lymphocytic leukemia (CLL) allow assessment of prognosis. However, the validity of current prognostic biomarkers based on a single assessment point remains unclear for patients who have survived one or more years. Conditional survival (CS) studies that address how prognosis may change over time, especially in prognostic subgroups, are still rare. We performed CS analyses to estimate 5-year survival in 1-year increments, stratified by baseline disease characteristics and known risk factors in two community-based cohorts of CLL patients (Freiburg University Hospital (n = 316) and Augsburg University Hospital (n = 564)) diagnosed between 1984 and 2021. We demonstrate that 5-year CS probability is stable (app. 75%) for the entire CLL patient cohort over 10 years. While age, sex, and stage have no significant impact on CS, patients with high-risk disease features such as non-mutated IGHV, deletion 17p, and high-risk CLL-IPI have a significantly worse prognosis at diagnosis, and 5-year CS steadily decreases with each additional year survived. Our results confirm that CLL patients have a stable survival probability with excess mortality and that the prognosis of high-risk CLL patients declines over time. We infer that CS-based prognostic information is relevant for disease management and counseling of CLL patients. [ABSTRACT FROM AUTHOR]

BackgroundConditional survival (CS) considers the duration since the initial diagnosis and can provide supplementary informative insights. Our objective was to evaluate CS among gliosarcoma (GSM) patients and develop a CS-incorporated nomogram to predict the conditional probability of survival.MethodsThis retrospective study using the Surveillance, Epidemiology, and End Results (SEER) database included patients with GSM between 2000 and 2017. The CS was defined as the probability of surviving additional y years after already surviving for x years. The formula utilized for CS was: CS(y|x) = S(y + x)/S(x), where S(x) denotes the overall survival at x years. Univariate Cox regression, best subset regression (BSR) and the least absolute shrinkage and selection operator (LASSO) were used for significant prognostic factors screening. Following this, backward stepwise multivariable Cox regression was utilized to refine predictor selection. Finally, a novel CS-integrated nomogram model was developed and we also employed diverse evaluation methods to assess its performance.ResultsThis study included a total of 1,015 GSM patients, comprising 710 patients in training cohort and 305 patients in validation cohort. CS analysis indicated a gradual increase in the probability of achieving a 5-year survival, ascending from 5% at diagnosis to 13, 31, 56, and 74% with each subsequent year survived after 1, 2, 3, and 4 years post-diagnosis, respectively. Following variable screening through univariate Cox regression, BSR, and LASSO analysis, five factors-age, tumor stage, tumor size, radiotherapy, and chemotherapy-were ultimately identified for constructing the CS-nomogram model. The performance of the nomogram model was validated through discrimination and calibration assessments in both the training and validation cohorts. Furthermore, we confirmed that the effectiveness of the CS-nomogram in stratifying GSM patient risk status.ConclusionThis nationwide study delineated the CS of patients diagnosed with GSM. Utilizing national data, a CS-nomogram could provide valuable guidance for patient counseling during follow-up and risk stratification.

Abstract Background Definitive chemoradiotherapy is one of the primary treatment modalities for older patients with esophageal cancer (EC). However, the evolution of prognosis over time and the factors affected non-EC deaths remain inadequately studied. We examined the conditional survival and annual hazard of death in older patients with EC after chemoradiotherapy. Methods We collected data from patients aged 65 or older with EC registered in the Surveillance, Epidemiology, and End Results database during 2000–2019. Conditional survival was defined as the probability of survival given a specific time survived. Annual hazard of death was defined the yearly event rate. Restricted cubic spline (RCS) analysis identified the association of age at diagnosis with mortality. Results Among 3739 patients, the 3-year conditional overall survival increased annually by 7-10%. Non-EC causes accounted for 18.8% of deaths, predominantly due to cardio-cerebrovascular diseases. The hazard of death decreased from 40 to 10% in the first 6 years and then gradually increased to 20% in the tenth year. Non-EC causes surpassed EC causes in hazard starting 5 years post-treatment. RCS indicated a consistent increase in death hazard with advancing age, following a linear relationship. The overall cohort was divided into two groups: 65–74 and ≥ 75 years old, with the ≥ 75-year-old group showing poorer survival and earlier onset of non-EC deaths (HR = 1.36, 95% CI: 1.15–1.62, P

Background: Definitive chemoradiotherapy is one of the primary treatment modalities for older patients with esophageal cancer (EC). However, the evolution of prognosis over time and the factors affected non-EC deaths remain inadequately studied. We examined the conditional survival and annual hazard of death in older patients with EC after chemoradiotherapy. Methods: We collected data from patients aged 65 or older with EC registered in the Surveillance, Epidemiology, and End Results database during 2000–2019. Conditional survival was defined as the probability of survival given a specific time survived. Annual hazard of death was defined the yearly event rate. Restricted cubic spline (RCS) analysis identified the association of age at diagnosis with mortality. Results: Among 3739 patients, the 3-year conditional overall survival increased annually by 7-10%. Non-EC causes accounted for 18.8% of deaths, predominantly due to cardio-cerebrovascular diseases. The hazard of death decreased from 40 to 10% in the first 6 years and then gradually increased to 20% in the tenth year. Non-EC causes surpassed EC causes in hazard starting 5 years post-treatment. RCS indicated a consistent increase in death hazard with advancing age, following a linear relationship. The overall cohort was divided into two groups: 65–74 and ≥ 75 years old, with the ≥ 75-year-old group showing poorer survival and earlier onset of non-EC deaths (HR = 1.36, 95% CI: 1.15–1.62, P < 0.001). Patients with early-stage disease (I-II) had higher risks of death from non-EC causes (HR = 0.82, 95% CI: 0.68–0.98, P = 0.035). Tumor histology had no significant impact on non-EC death risk (HR = 1.17, 95% CI: 0.98–1.39, P = 0.081). Conclusions: Survival probability increases with time for older patients with EC treated with chemoradiotherapy. Clinicians and patients should prioritize managing and preventing age-related comorbidities, especially in older cohorts and those with early-stage disease. [ABSTRACT FROM AUTHOR]

Background: As the form of World Health Organization Central Nervous System (WHO CNS) tumor classifications is updated, there is a lack of research on outcomes for intracranial combined solitary-fibrous tumor and hemangiopericytoma (SFT/HPC). This study aimed to explore conditional survival (CS) pattern and develop a survival prediction tool for intracranial SFT/HPC patients. Methods: Data of intracranial SFT/HPC patients was gathered from the Surveillance, Epidemiology, and End Results (SEER) program of the National Cancer Institute. The patients were split into training and validation groups at a 7:3 ratio for our analysis. CS is defined as the likelihood of surviving for a specified period of time (y years), given that the patient has survived x years after initial diagnosis. Then, we used this definition of CS to analyze the intracranial SFT/HPC patients. The least absolute shrinkage and selection operator (LASSO) regression and best subset regression (BSR) were employed to identify predictive factors. The Multivariate Cox regression analysis was applied to establish a novel CS-based nomogram, and a risk stratification system was developed using this model. Results: From the SEER database, 401 patients who were diagnosed with intracranial SFT/HPC between 2000 and 2019 were identified. Among them, 280 were included in the training group and 121 were included in the internal validation group for analysis. Our study revealed that in intracranial SFT/HPC, 5-year survival rates saw significant improvement ranging from 78% at initial diagnosis to rates of 83%, 87%, 90%, and 95% with each successive year after surviving for 1–4 years. The LASSO regression and BSR identified patient age, tumor behavior, surgery and radiotherapy as predictors of CS-based nomogram development. A risk stratification system was also successfully constructed to facilitate the identification of high-risk patients. Conclusion: The CS pattern of intracranial SFT/HPC patients was outlined, revealing a notable improvement in 5-year survival rates after an added period of survival. Our newly-established CS-based nomogram and risk stratification system can provide a real-time dynamic survival estimation and facilitate the identification of high-risk patients, allowing clinicians to better guide treatment decision for these patients. [ABSTRACT FROM AUTHOR]

Background: Infected pancreatic necrosis (IPN) is a severe complication of acute pancreatitis, with mortality rates ranging from 15 to 35%. However, limited studies exist to predict the survival of IPN patients and nomogram has never been built. This study aimed to identify predictors of mortality, estimate conditional survival (CS), and develop a CS nomogram and logistic regression nomogram for real-time prediction of survival in IPN patients. Methods: A prospective cohort study was performed in 335 IPN patients consecutively enrolled at a large Chinese tertiary hospital from January 2011 to December 2022. The random survival forest method was first employed to identify the most significant predictors and capture clinically relevant nonlinear threshold effects. Instantaneous death risk and CS was first utilized to reveal the dynamic changes in the survival of IPN patients. A Cox model-based nomogram incorporating CS and a logistic regression-based nomogram were first developed and internally validated with a bootstrap method. Results: The random survival forest model identified seven foremost predictors of mortality, including the number of organ failures, duration of organ failure, age, time from onset to first intervention, hemorrhage, bloodstream infection, and severity classification. Duration of organ failure and time from onset to first intervention showed distinct thresholds and nonlinear relationships with mortality. Instantaneous death risk reduced progressively within the first 30 days, and CS analysis indicated gradual improvement in real-time survival since diagnosis, with 90-day survival rates gradually increasing from 0.778 to 0.838, 0.881, 0.974, and 0.992 after surviving 15, 30, 45, 60, and 75 days, respectively. After further variables selection using step regression, five predictors (age, number of organ failures, hemorrhage, time from onset to first intervention, and bloodstream infection) were utilized to construct both the CS nomogram and logistic regression nomogram, both of which demonstrated excellent performance with 1000 bootstrap. Conclusion: Number of organ failures, duration of organ failure, age, time from onset to first intervention, hemorrhage, bloodstream infection, and severity classification were the most crucial predictors of mortality of IPN patients. The CS nomogram and logistic regression nomogram constructed by these predictors could help clinicians to predict real-time survival and optimize clinical decisions. [ABSTRACT FROM AUTHOR]

IntroductionThe fight against SARS-CoV-2 has been a major task worldwide since it was first identified in December 2019. An imperative preventive measure is the availability of efficacious vaccines while there is also a significant interest in the protective effect of a previous SARS-CoV-2 infection on a subsequent infection (natural protection rate).MethodsIn order to compare protection rates after infection and vaccination, researchers consider different effect measures such as 1 minus hazard ratio, 1 minus odds ratio, or 1 minus risk ratio. These measures differ in a setting with competing risks. Nevertheless, as there is no unique definition, these metrics are frequently used in studies examining protection rate. Comparison of protection rates via vaccination and natural infection poses several challenges. For instance many publications consider the epidemiological definition, that a reinfection after a SARS-CoV-2 infection is only possible after 90 days, whereas there is no such constraint after vaccination. Furthermore, death is more prominent as a competing event during the first 90 days after infection compared to vaccination. In this work we discuss the statistical issues that arise when investigating protection rates comparing vaccination with infection. We explore different aspects of effect measures and provide insights drawn from different analyses, distinguishing between the first and the second 90 days post-infection or vaccination.ResultsIn this study, we have access to real-world data of almost two million people from Stockholm County, Sweden. For the main analysis, data of over 52.000 people is considered. The infected group is younger, includes more men, and is less morbid compared to the vaccinated group. After the first 90 days, these differences increased. Analysis of the second 90 days shows differences between analysis approaches and between age groups. There are age-related differences in mortality. Considering the outcome SARS-CoV-2 infection, the effect of vaccination versus infection varies by age, showing a disadvantage for the vaccinated in the younger population, while no significant difference was found in the elderly.DiscussionTo compare the effects of immunization through infection or vaccination, we emphasize consideration of several investigations. It is crucial to examine two observation periods: The first and second 90-day intervals following infection or vaccination. Additionally, methods to address imbalances are essential and need to be used. This approach supports fair comparisons, allows for more comprehensive conclusions and helps prevent biased interpretations.

Background: Conditional survival (CS) analyses provide an estimate of survival accounting for years already survived after treatment. We aim to evaluate the difference between actuarial and conditional survival in patients following lung resection for non–small cell lung cancer (NSCLC). In addition, CS analyses are used to examine whether prognosticators of survival change over time following surgery. Methods: Patients who underwent anatomic lung resection at a single institution for pathologic stage I-IIIA NSCLC between 2010 and 2021 were identified; those who underwent wedge resection for node-negative tumors ≤2 cm were also included. CS estimates were calculated as the probability of remaining disease-free after x years of nonrecurrence (CSx). Kaplan–Meier, log-rank, and Cox proportional hazard methods for examining CS were used for subgroup comparisons and assessing associations with baseline covariates. Results: Overall, 863 patients met the study inclusion criteria, with a median follow-up of 44.1 months. Conditional overall survival (OS) and disease-free survival (DFS) were greater than actuarial rates at all time points after surgery. At the time of resection, male sex (hazard ratio [HR], 1.33; 95% confidence interval [CI], 1.03 to 1.72; P = .032), tumor size >3 cm (HR, 1.17; 95% CI, 1.11-1.23; P

Abstract Background Little is known about death hazard and conditional survival of oncocytic cell carcinoma of the thyroid (OCC). Methods Patients diagnosed with OCC between 2004 to 2019 were obtained from the Surveillance, Epidemiology, and End Results (SEER) database. The Kaplan–Meier method was used to estimate the actuarial disease-specific survival (DSS). The annual hazard rate of death was depicted employing the hazard function. Based on the life-table method, the conditional DSS was calculated. Results In terms of DSS rates, there were statistically significant differences among the different stages (P

Abstract Background The long-term dynamic recurrence hazard of locally advanced gastric cancer (LAGC) in the clinical setting of adjuvant chemotherapy (ACT) remains unclear. Purpose This study aimed to investigate the dynamic recurrence risk of LAGC in patients who received ACT or not. Methods The study assessed data from patients with LAGC who underwent radical gastrectomy between January, 2010 and October, 2015. Inverse probability of treatment weighting (IPTW) was performed to reduce selection bias between the ACT and observational (OBS) groups. Conditional recurrence-free survival (cRFS) and restricted mean survival time (RMST) were used to assess the survival differences. Results In total, 1,661 LAGC patients were included (ACT group, n = 1,236 and OBS group, n = 425). The recurrence hazard gradually declined; in contrast, cRFS increased with RFS already accrued. Following IPTW adjustment, the cRFS rates were higher in the ACT group than those in the OBS group for patients at baseline or with accrued RFS of 1 and 2 years (p˂0.05). However, the cRFS rates of the ACT group were comparable with those of the OBS group for patients with accrued RFS of 3 or more years (p > 0.05). Likewise, the 5-year △RMST between the ACT and OBS groups demonstrated a similar trend. Moreover, the hematological metastasis rate of the ACT group was significantly lower than that of the OBS group for patients at baseline or with accrued RFS of 1 and 2 years, respectively (p˂0.05). Conclusions Although ACT could provide substantial benefits for patients with LAGC, the differences in recurrence hazard between the ACT and OBS groups may attenuate over time, which could help guide surveillance and alleviate patients’ anxiety. Further prospective large-scale studies are warranted.

Abstract Background Survival in breast cancer (BC) has developed favorably but late recurrences are still a problem. Methods We model survival data from the NORDCAN database and analyze 1‐, 5‐, and 10‐year relative survival and 5/1‐ and 10/5‐year conditional survival in BC from Denmark (DK), Finland (FI), Norway (NO), and Sweden (SE) between 1971 and 2020. Conditional survival measures survival in those who had survived year 1 to reach year 5 (5/1), or in those who had survived year 5 to reach year 10 (10/5). Results Almost all survival metrics were best for SE but survival in all countries improved in the course of time approaching the SE levels which were 98.3% for 1‐year, 92.3% for 5‐year, and 87.8% for 10‐year survival. Conditional 10/5‐year survival, covering 5 years, was better than 5/1‐year survival, covering 4 years. A contributing factor is most likely the high rate of recurrence in period 2–5 years. The difference was observed for all countries but for DK 10/5‐year survival approached 1‐year survival and for NO and SE 10/5‐year survival was only barely better than 5/1‐year survival. The explanation to this was the excellent 10/5‐year survival in DK compared to SE and particularly to NO. Literature search suggested that the reason for the relatively low 10/5‐year survival in NO might be stagnant survival development in old patients. Conclusions We assume that late mortality is critically limiting survival in BC and either interference with the late metastatic process or effective treatment will be key to future improvements in BC survival.

BackgroundMerkel cell carcinoma (MCC) is a rare type of invasive neuroendocrine skin malignancy with high mortality. However, with years of follow-up, what is the actual survival rate and how can we continually assess an individual’s prognosis? The purpose of this study was to estimate conditional survival (CS) for MCC patients and establish a novel CS-based nomogram model.MethodsThis study collected MCC patients from the Surveillance, Epidemiology, and End Results (SEER) database and divided these patients into training and validation groups at the ratio of 7:3. CS refers to the probability of survival for a specific timeframe (y years), based on the patient’s survival after the initial diagnosis (x years). Then, we attempted to describe the CS pattern of MCCs. The Least absolute shrinkage and selection operator (LASSO) regression was employed to screen predictive factors. The Multivariate Cox regression analysis was applied to demonstrate these predictors’ effect on overall survival and establish a novel CS-based nomogram.ResultsA total of 3,843 MCC patients were extracted from the SEER database. Analysis of the CS revealed that the 7-year survival rate of MCC patients progressively increased with each subsequent year of survival. The rates progressed from an initial 41–50%, 61, 70, 78, 85%, and finally to 93%. And the improvement of survival rate was nonlinear. The LASSO regression identified five predictors including patient age, sex, AJCC stage, surgery and radiotherapy as predictors for CS-nomogram development. And this novel survival prediction model was successfully validated with good predictive performance.ConclusionCS of MCC patients was dynamic and increased with time since the initial diagnosis. Our newly established CS-based nomogram can provide a dynamic estimate of survival, which has implications for follow-up guidelines and survivorship planning, enabling clinicians to guide treatment for these patients better.

Introduction: With recent advances in breast cancer (BC) treatment, the disease-free survival (DFS) of patients is increasing and the risk factors for recurrence and metastasis are changing. However, a dynamic approach to assessing the risk of recurrent metastasis in BC is currently lacking. This study aimed to develop a dynamically changing prediction model for recurrent metastases based on conditional survival (CS) analysis. Methods: Clinical and pathological data from patients with BC who underwent surgery at the Affiliated Hospital of Qingdao University between August 2011 and August 2022 were retrospectively analysed. The risk of recurrence and metastasis in patients with varying survival rates was calculated using CS analysis, and a risk prediction model was constructed. Results: A total of 4244 patients were included in this study, with a median follow-up of 83.16 ± 31.59 months. Our findings suggested that the real-time DFS of patients increased over time, and the likelihood of DFS after surgery correlated with the number of years of prior survival. We explored different risk factors for recurrent metastasis in baseline patients, 3-year, and 5-year disease-free survivors, and found that low HER2 was a risk factor for subsequent recurrence in patients with 5-year DFS. Based on this, conditional nomograms were developed. The nomograms showed good predictive ability for recurrence and metastasis in patients with BC. Conclusion: Our study showed that the longer patients with BC remained disease-free, the greater their chances of remaining disease-free again. Predictive models for recurrence and metastasis risk based on CS analysis can help improve the confidence of patients fighting cancer and help doctors personalise treatment and follow-up plans. Plain language summary: Conditional survival in breast cancer With recent advances in breast cancer (BC) treatment, the disease-free survival of patients is increasing and the risk factors for recurrence and metastasis are changing. One of the key risk factor is the human epidermal growth factor receptor 2 (HER2). However, the recent advent of anti-HER2 antibody-drug conjugates (ADC) has challenged the traditional binary classification based on HER2. Patients in the traditional HER2-negative group can now be further classified as HER2-low (ISH-negative with IHC1 or IHC2) or HER2-0 (ISH-negative and IHC-0). Does this categorisation also have some value for the prognosis of BC? To figure this out, we retrospectively analysed the clinical and pathological data of BC patients who underwent surgery at the Affiliated Hospital of Qingdao University between August 2011 and August 2022. The risk of recurrence and metastasis in patients with varying survival rates was calculated using conditional survival analysis, and a risk prediction model was constructed.Our findings suggested that the real-time disease-free survival (DFS) of patients increased over time, and the likelihood of DFS after surgery correlated with the number of years of prior survival. Conditional nomograms were developed for baseline patients, 3-year and 5-year disease-free survivors. The nomograms showed good predictive ability for recurrence and metastasis in patients with BC. [ABSTRACT FROM AUTHOR]

An important question in determining long-term prognosis for women with ovarian cancer is whether risk of death changes the longer a woman lives. Large real-world datasets permit assessment of conditional survival (CS) given both prior overall survival (OS) and real-world progression-free survival (rwPFS). Using a longitudinal dataset from US oncology centers, this study included 6778 women with ovarian cancer. We calculated CS rates as the Kaplan-Meier probability of surviving an additional 1 or 5 years, given no mortality (OS) or disease progression (rwPFS) event in the previous 0.5–5 years since first-line chemotherapy initiation, adjusted for factors associated with OS based on multivariable Cox regression. Median study follow-up was 9 years (range, 1–44) from first-line initiation to data cutoff (17-Feb-2021). Median OS was 58.0 months (95% CI, 54.9–60.8); median rwPFS was 18.4 months (17.4–19.4). The adjusted 1-year CS rate (ie, rate of 1 year additional survival) did not vary based on time alive, whereas the adjusted 5-year CS rate increased from 48.5% (47.0%–50.1%) for women who had already survived 6 months to 66.4% (63.3%–69.6%) for those already surviving 5 years (thus surviving 10 years total). The adjusted 1-year CS rate increased from 90.4% (89.5%–91.4%) with no rwPFS event at 6 months to 97.6% (96.4%–98.8%) with no rwPFS event at 5 years; adjusted 5-year CS rate increased from 53.7% (52.0%–55.5%) to 85.0% (81.2%–88.9%), respectively. This analysis extends the concept of CS by also conditioning on time progression-free. Patients with longer rwPFS experience longer survival than patients with shorter rwPFS. • Women with ovarian cancer have an increasing probability of survival with increasing time survived after the diagnosis. • Conditional survival (CS) is the probability of surviving + y years, given already having survived x years post-diagnosis. • The 5-year CS rate increased from 54% for survival with no disease progression at 6 mos to 85% with no progression at 5 yrs. • The prognosis for ovarian cancer improved substantially with time for women alive without disease progression. [ABSTRACT FROM AUTHOR]

Background: Cancers of the head and neck (HN) are heterogeneous tumors with incidence rates varying globally. In Northern Europe oral and oropharyngeal cancers are the most common individual types. Survival for HN varies by individual tumor type but for most of them survival trends are not well known over extended periods of time. Methods: Data for a retrospective survival study were obtained for Danish, Finnish, Norwegian, and Swedish patients from the NORDCAN database from 1971 to 2020. Relative 1- and 5-year survival rates and 5/1-year conditional survival for years 2–5 were calculated. Results: Both 1- and 5-year survival improved for all HN cancers but only marginally for laryngeal cancer. For the other cancers a 50-year increase in 5-year survival was about 30% units for nasopharyngeal and oropharyngeal cancers, 20% units for oral cancer and somewhat less for hypopharyngeal cancer. Conclusions: 5-year survival reached about 65% for all HN cancers, except for hypopharyngeal cancer (30%). Human papilloma virus infection is becoming a dominant risk factor for the rapidly increasing oropharyngeal cancer, the prevention of which needs to emphasize oral sex as a route of infection. [ABSTRACT FROM AUTHOR]

Follicular dendritic cell sarcoma (FDCS) is a rare low-intermediate grade malignant neoplasm. To date, published data on FDCS clinical courses are sparse, and no conditional survival study has been performed. Thus, we retrospectively analyzed 187 patients diagnosed with FDCS from the Surveillance, Epidemiology, and End Results (SEER) database. In this study, the median age at diagnosis was 50 years and 91 (48.7%) patients were male. The most common primary location was the abdomen/pelvis (82, 43.9%). The 1-year, 3-year, and 5-year overall survival (OS) were 88.7%, 69.0%, and 59.8%, respectively. The 5-year conditional overall survival increased from 65.7% at baseline to 83.8% in 5-year survivors. The 3-year FDCS-specific death rate was 26.7% and the rate of death from other reasons was 3.7%. In addition, the annual death hazard was the highest in the first four years after diagnosis and increased again in the 7th and 8th years. Age > 60 years at diagnosis, metastatic disease, and FDCS in thoracic organs were associated with shorter OS and FDCS-specific survival. In addition, FDCS patients, with either local or metastatic disease, could benefit from surgery therapy. In addition, adjuvant radiotherapy or chemotherapy for local disease provided no significant improvement in overall survival or FDCS-specific survival. We hope these findings may guide treatments and surveillance strategies for FDCS patients in clinical practice. [ABSTRACT FROM AUTHOR]

Objective: To investigate the long-term dynamics of recurrence risk and the significance of prognostic variables using conditional recurrence-free survival (C-RFS) analysis in neoadjuvant treatment (NAT) for resectable (R) and borderline resectable (BR) pancreatic cancer (PC). Background: C-RFS analysis assesses the probability of achieving additional RFS according to the RFS already accrued. Methods: Patients with NAT and subsequent resection for R/BRPC were enrolled. In the C-RFS analysis, the actual 5-year RFS (5yRFS) rate was calculated separately in the subgroup that had already gained a given amount of RFS. The significance levels of prognostic variables associated with 5yRFS were assessed regarding their time-dependent dynamics in a conditional fashion. Results: Among the total 397 patients, 160 survived for more than 5 years without recurrence after surgery (actual 5yRFS rate: 45%). The probability of 5yRFS incrementally increased based on the RFS already accrued. Pathological nodal and vascular involvement were significant influencers of 5yRFS. The patients with nodal involvement consistently remained at significantly higher risk of recurrence than those without, even after 5yRFS, whereas positivity of vascular involvement was significantly associated with the risk of recurrence only during the early postoperative period and lost its significance after 3yRFS accrued. Conclusions: In NAT for R/BRPC, the probability of gaining additional RFS increases as a function of RFS already accrued, and the significance of prognostic variables time-dependently evolves in their own patterns during the long-term postoperative period. [ABSTRACT FROM AUTHOR]

Background: Little is known about death hazard and conditional survival of oncocytic cell carcinoma of the thyroid (OCC). Methods: Patients diagnosed with OCC between 2004 to 2019 were obtained from the Surveillance, Epidemiology, and End Results (SEER) database. The Kaplan–Meier method was used to estimate the actuarial disease-specific survival (DSS). The annual hazard rate of death was depicted employing the hazard function. Based on the life-table method, the conditional DSS was calculated. Results: In terms of DSS rates, there were statistically significant differences among the different stages (P < 0.01). Annual hazard curves for mortality from OCC in the entire study participants demonstrated an overall decreasing tendency with two peaks at 3 and 10 years. In patients with distant disease, the death risk curve was the steepest and decreased quickly and evidently. Conditional DSS tended to increase over time in the entire study population. Patients with distant disease showed more significant alterations than those patients with local or regional disease. Conclusions: Prognosis improved over time in patients with OCC. The largest increase in conditional DSS was observed in patients with distant disease. Conditional survival may provide more relevant prognostic information than conventional survival estimates and allow personalized follow-up and counseling. Key points: Questions: How do the risk of death and survival probability change over time in patients with oncocytic cell carcinoma of the thyroid (OCC)? Findings: In this retrospective study of 3401 patients, prognosis improves over time in patients with OCC of different Surveillance, Epidemiology, and End Results (SEER) stages. The greatest improvement was observed in patients with distant disease. Meaning: For OCC survivors, death hazard and conditional survival analysis provide more accurate dynamic estimates of survival than conventional survival analysis for patients who have survived a period of time after diagnosis. With such information, clinicians can provide an accurate risk assessment of survival and formulate individual treatment and surveillance recommendations for patients diagnosed with OCC. [ABSTRACT FROM AUTHOR]

Background: Recent studies have reported that overall survival of elderly patients with primary central nervous system lymphoma (PCNSL), who have the highest incidence of this disease, had failed to benefit from the advancements in treatment strategies over the past decades. This highlights the necessity for intensified research to guide treatment decisions for this specific patient population. Methods: The Surveillance, Epidemiology, and End Results (SEER) program of the National Cancer Institute (NCI) was used to extract data of elderly PCNSL patients (age ≥ 60) who were divided into training and validation groups at the ratio of 7:3, for our analysis. Conditional survival [CS(y|x)] was defined as the probability at survival additional y years given that the patient had not died of PCNSL at a specified period of time (x years) after initial diagnosis. The CS pattern of elderly PCNSL patients was analyzed. The least absolute shrinkage and selection operator (LASSO) regression and multivariate Cox regression analysis were applied to develop a novel CS-based nomogram. Results: A total of 3315 elderly patients diagnosed with CNS lymphoma between 2000 and 2019 were extracted from the SEER database, of whom 2320 patients were divided into the training group and 995 into the internal validation group. CS analysis revealed a noteworthy escalation in the 5-year survival rate among elderly PCNSL patients for every additional year of survival. The rates progressed from an initial 21–49%, 63%, and 75%, culminating in an impressive 88% and the survival improvement over time was nonlinear. The LASSO regression identified nine predictors and multivariate Cox regression was used to successfully construct the CS-based nomogram model with favorable prediction performance. Conclusion: CS of elderly PCNSL patients was dynamic and increased over time. Our newly-established CS-based nomogram can provide a real-time dynamic survival estimation, allowing clinicians to better guide treatment decision for these patients. [ABSTRACT FROM AUTHOR]

Abstract 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.

Filip Tichanek,1,2 Asta Försti,3,4 Otto Hemminki,5,6 Akseli Hemminki,5,7 Kari Hemminki1,8 1Biomedical Center, Faculty of Medicine, Charles University Pilsen, Pilsen, 30605, Czech Republic; 2Institute of Pathological Physiology, Faculty of Medicine in Pilsen, Charles University, Pilsen, Czech Republic; 3Hopp Children’s Cancer Center (KiTZ), Heidelberg, Germany; 4Division of Pediatric Neurooncology, German Cancer Research Center (DKFZ), German Cancer Consortium (DKTK), Heidelberg, Germany; 5Cancer Gene Therapy Group, Translational Immunology Research Program, University of Helsinki, Helsinki, Finland; 6Department of Urology, Helsinki University Hospital, Helsinki, Finland; 7Comprehensive Cancer Center, Helsinki University Hospital, Helsinki, Finland; 8Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, GermanyCorrespondence: Kari Hemminki, Email k.hemminki@dkfz.deObjective: Lung cancer is often diagnosed at an advanced stage and survival has been poor, although long-term studies have been rare. We analyzed data on survival in lung cancer from Denmark, Finland, Norway, and Sweden over a 50-year period (1971– 2020).Methods: Relative 1- and 5-year survival data were obtained from the NORDCAN database for 1971– 2020. We used generalized additive models to estimate survival trends over time and uncertainty of these estimates. We additionally calculated conditional survival from the 1st to 5th year (5/1-year), estimated annual changes in survival rates, and determined significant breaking points.Results: In 2016– 2020, 5-year survival rate for lung cancer was best for Norwegian men (26.6%) and women (33.2%). The sex difference was significant and it was found for each country. Survival improved modestly until the year 2000, after which time survival curves increased steeply and kept the linear shape to the end of follow-up, indicating consistent improvement in survival. Survival curves for 1- and 5/1-year survival were almost superimposable, indicating that deaths in the first year were approximately as many as in the subsequent 4 years, thus marking sustained long-term survival.Conclusion: We could document a positive development in lung cancer survival with steep upward trends after the year 2000. Intensions for curative treatment have been increasing and the outcomes have been improving with the help of novel imaging methods. Pathways for facile patient access to treatment have been instituted. Close to 90% of the patients are ever smokers. National anti-smoking acts and alerting people who smoke about early symptoms may be beneficial, as metastatic lung cancer remains difficult to cure.Keywords: smoking, lung cancer, relative survival, conditional survival, treatment, surgery

Background: The long-term dynamic recurrence hazard of locally advanced gastric cancer (LAGC) in the clinical setting of adjuvant chemotherapy (ACT) remains unclear. Purpose: This study aimed to investigate the dynamic recurrence risk of LAGC in patients who received ACT or not. Methods: The study assessed data from patients with LAGC who underwent radical gastrectomy between January, 2010 and October, 2015. Inverse probability of treatment weighting (IPTW) was performed to reduce selection bias between the ACT and observational (OBS) groups. Conditional recurrence-free survival (cRFS) and restricted mean survival time (RMST) were used to assess the survival differences. Results: In total, 1,661 LAGC patients were included (ACT group, n = 1,236 and OBS group, n = 425). The recurrence hazard gradually declined; in contrast, cRFS increased with RFS already accrued. Following IPTW adjustment, the cRFS rates were higher in the ACT group than those in the OBS group for patients at baseline or with accrued RFS of 1 and 2 years (p˂0.05). However, the cRFS rates of the ACT group were comparable with those of the OBS group for patients with accrued RFS of 3 or more years (p > 0.05). Likewise, the 5-year △RMST between the ACT and OBS groups demonstrated a similar trend. Moreover, the hematological metastasis rate of the ACT group was significantly lower than that of the OBS group for patients at baseline or with accrued RFS of 1 and 2 years, respectively (p˂0.05). Conclusions: Although ACT could provide substantial benefits for patients with LAGC, the differences in recurrence hazard between the ACT and OBS groups may attenuate over time, which could help guide surveillance and alleviate patients' anxiety. Further prospective large-scale studies are warranted. [ABSTRACT FROM AUTHOR]

Background: The aim of this study was to clarify the improvement of the overall survival (OS) over time in young non-metastatic nasopharyngeal carcinoma (NPC) survivors by conditional survival (CS) analysis and to construct a CS-nomogram for updating individualized real-time prognosis. Methods: The study included 3409 young non-metastatic NPC patients from the Surveillance, Epidemiology, and End Results (SEER) database (2004–2019). OS was estimated using the Kaplan–Meier method. CS was calculated based on CS(y|x) = OS(y + x)/OS(x), defined as the probability that a patient would survive for another y years after surviving for x years since diagnosis. We identified predictors using the least absolute shrinkage and selection operator (LASSO) regression and developed the CS-nomogram using multivariate Cox regression and the CS formula. Results: CS analysis showed a continuous increase in 10-year OS for young non-metastatic NPC from the initial 60.4% to 65.0%, 70.2%, 74.2%, 78.2%, 82.6%, 86.9%, 91.1%, 96.2% and 97.0% (surviving 1–9 years after diagnosis, respectively). After screening by LASSO regression, age, race, marital status, histological type, T- and N-status were used as predictors to construct the CS-nomogram. The model accurately estimated the real-time prognosis of survivors during follow-up with a stable time-dependent area under the curve (AUC). Conclusions: CS analysis based on SEER database calibrated the real-time prognosis of young non-metastatic NPC survivors, revealing a dynamic improvement during follow-up time. We developed a novel CS-nomogram to update survival data for real-time optimization of monitoring strategies, medical resource allocation, and patient counseling. However, it was important to note that the model still needed external data validation and continuous improvement. [ABSTRACT FROM AUTHOR]

Simple Summary: Male cancers include common prostate cancer (PC) and the much rarer testicular (TC) and penile cancers. Recent survival data for these cancers are relatively good, but long-term studies are rare. To analyzed relative survival in these cancers, we used the NORDCAN database with information from Denmark, Finland, Norway, and Sweden over a 50-year period (1971–2020). Survival improved early for TC, and 5-year survival reached 90% after 1985. Towards the end of the follow-up, TC patients who had survived the 1st year survived the next 4 years with a comparable probability to the background population. For PC, 90% survival was reached after 2000. For penile cancer, 5-year survival never reached 90%, and the improvements in survival were modest at best. As conclusions, more than 90% of the patients diagnosed with PC and TC are alive 5 years later compared to men in general. For penile cancer, mortality is higher, and early symptoms should be discussed with the doctor. Survival studies are important tools for cancer control, but long-term survival data on high-quality cancer registries are lacking for all cancers, including prostate (PC), testicular (TC), and penile cancers. Using generalized additive models and data from the NORDCAN database, we analyzed 1- and 5-year relative survival for these cancers in Denmark (DK), Finland (FI), Norway (NO), and Sweden (SE) over a 50-year period (1971–2020). We additionally estimated conditional 5/1-year survival for patients who survived the 1st year after diagnosis. Survival improved early for TC, and 5-year survival reached 90% between 1985 (SE) and 2000 (FI). Towards the end of the follow-up, the TC patients who had survived the 1st year survived the next 4 years with comparable probability to the background population. For PC, the 90% landmark was reached between 2000 (FI) and after 2010 (DK). For penile cancer, 5-year survival never reached the 90% landmark, and the improvements in survival were modest at best. For TC, early mortality requires attention, whereas late mortality should be tackled for PC. For penile cancer, the relatively high early mortality may suggest delays in diagnosis and would require more public awareness and encouragement of patients to seek medical opinion. In FI, TC and penile cancer patients showed roughly double risk of dying compared to the other Nordic countries, which warrants further study and clinical attention. [ABSTRACT FROM AUTHOR]

Background: Survival in breast cancer (BC) has developed favorably but late recurrences are still a problem. Methods: We model survival data from the NORDCAN database and analyze 1‐, 5‐, and 10‐year relative survival and 5/1‐ and 10/5‐year conditional survival in BC from Denmark (DK), Finland (FI), Norway (NO), and Sweden (SE) between 1971 and 2020. Conditional survival measures survival in those who had survived year 1 to reach year 5 (5/1), or in those who had survived year 5 to reach year 10 (10/5). Results: Almost all survival metrics were best for SE but survival in all countries improved in the course of time approaching the SE levels which were 98.3% for 1‐year, 92.3% for 5‐year, and 87.8% for 10‐year survival. Conditional 10/5‐year survival, covering 5 years, was better than 5/1‐year survival, covering 4 years. A contributing factor is most likely the high rate of recurrence in period 2–5 years. The difference was observed for all countries but for DK 10/5‐year survival approached 1‐year survival and for NO and SE 10/5‐year survival was only barely better than 5/1‐year survival. The explanation to this was the excellent 10/5‐year survival in DK compared to SE and particularly to NO. Literature search suggested that the reason for the relatively low 10/5‐year survival in NO might be stagnant survival development in old patients. Conclusions: We assume that late mortality is critically limiting survival in BC and either interference with the late metastatic process or effective treatment will be key to future improvements in BC survival. [ABSTRACT FROM AUTHOR]

Abstract Background Steady evolution of therapies has improved prognosis of patients with multiple myeloma (MM) over the past two decades. Yet, knowledge about survival trends and causes of death in MM might play a crucial role in long-term management of this patient collective. Here, we investigate time trends in myeloma-specific survival at the population level over two decades and analyse causes of death in times of prolonged survival. Methods Age-standardised and age group-specific relative survival (RS) of MM patients aged

Survival in melanoma has been increasing and the most recent interest is to observe the population-level impact of novel targeted therapies and immunotherapy. We analysed survival in melanoma from Denmark (DK), Finland (FI), Norway (NO) and Sweden (SE) over a 50-years period (1971–2020). Relative 1–5/1- and 5-year survival data were obtained from the NORDCAN database for the years 1971–2020. We estimated annual changes in survival rates and determined significant breaking points for trends. Survival in melanoma has reached the point where 1-year survival is approaching 100% (men 97.5–98.6%, women 98.4–99.3%, depending on the country) and 5-year survival is 93% for men (91.5–95.2%) and 96% for women (95.3–97.2%). The highest survival figures were for DK. Significant increases in both 1- and 5-year survival were observed in most countries even towards the end of the follow-up (from 2006 to 2010–2011–2015 and further to 2016–2020). The main increase in melanoma survival took place up to year 1990, which was probably largely achieved through successful population campaigns for sun protection and programmes for early detection of lesions. Survival increased again after year 2000 up to the last period 2016–2020. This late development coincided with the introduction of targeted therapies using BRAF and BRAF/MEK inhibitors, and towards the end of the time period availability of checkpoint inhibitors. The success of melanoma treatment in DK was mostly likely due to the efficient use of modern therapies and to the centralised treatment for metastatic disease. • Survival in melanoma has increased, as we report here from the Nordic countries. • Metastatic melanoma, 10% of all, was previously not curable. • Novel therapies for metastatic melanoma include targeted and immunotherapies. • Metastatic melanoma has responded well to immunotherapies prompting wide use. • Our encouraging recent survival figures may in part depend on immunotherapies. [ABSTRACT FROM AUTHOR]

Simple Summary: Cancers in the urinary bladder and kidney are common in men and rarer in women. Cigarette smoking is a shared risk factor for both of these cancers. Some 50 years ago, survival in these cancers was low, and it was worse for kidney than bladder cancer. In the present study, we could show improvement in survival for these cancers in the Nordic countries, and similar improvements have also been observed in other countries. Kidney cancer survival improved remarkably well, as 50 years ago, only 20–30% of the patients survived 5 years, but currently, some 75% survive 5 years. In male bladder cancer, 5-year survival is still somewhat better than survival in kidney cancer, but female kidney cancer survival has caught up with that of bladder cancer. The reasons for this positive development for both of these cancers is earlier diagnosis as patients with blood in urine are readily taken for examinations. Additionally, treatment has become more efficient, and continuously new medications are being introduced. Kidney and bladder cancers share etiology and relatively good recent survival, but long-term studies are rare. We analyzed survival for these cancers in Denmark, Finland, Norway (NO), and Sweden (SE) over a 50-year period (1971–2020). Relative 1- and 5-year survival data were obtained from the NORDCAN database, and we additionally calculated conditional 5/1-year survival. In 2016–2020, 5-year survivals for male kidney (79.0%) and bladder (81.6%) cancers were best in SE. For female kidney cancer, NO survival reached 80.0%, and for bladder cancer, SE survival reached 76.1%. The magnitude of 5-year survival improvements during the 50-year period in kidney cancer was over 40% units; for bladder cancer, the improvement was over 20% units. Survival in bladder cancer was worse for women than for men, particularly in year 1. In both cancers, deaths in the first year were approximately as many as in the subsequent 4 years. We could document an impressive development for kidney cancer with tripled male and doubled female 5-year survival in 50 years. Additionally, for bladder cancer, a steady improvement was recorded. The current challenges are to curb early mortality and target treatment to reduce long-term mortality. [ABSTRACT FROM AUTHOR]

Introduction: Cervical spine fractures with severe spinal cord injury (SCI) are common following cervical spine trauma and are associated with a high mortality rate. Understanding the mortality patterns of patients with cervical spine fractures and severe SCI can offer valuable evidence to surgeons and family members who are required to make critical healthcare decisions. The authors aimed to evaluate the instantaneous death risk and conditional survival (CS) of such patients and developed conditional nomograms to account for different periods of survivors and predict the survival rates. Methods: Their instantaneous death risks were calculated using the hazard function, and the Kaplan-Meier method was used to evaluate the survival rates. Cox regression was used to choose the variables for the construction of the nomograms. The area under the receiver operating characteristic curve and calibration plots were used to validate the performance of the nomograms. Results: The authors finally included 450 patients with cervical spine fractures and severe SCI using propensity score matching. The instantaneous death risk was the highest during the first 12 months after injury. Surgical treatment can help decrease the instantaneous death risk quickly, especially in early-term surgery. The 5-year CS increased constantly from 73.3% at baseline to 88.0% after 2 years of survival. Conditional nomograms were constructed at baseline and in those who survived for 6 and 12 months. The area under the receiver operating characteristic curve and calibration curves indicated that the nomograms had a good performance. Conclusion: Their results improve our understanding of the instantaneous death risk of patients in different periods following injury. CS demonstrated the exact survival rate among medium-term and long-term survivors. Conditional nomograms are suitable for different survival periods in predicting the probability of survival. Conditional nomograms help in understanding the prognosis and improve the shared decision-making approaches. [ABSTRACT FROM AUTHOR]

Abstract Background Liver cancer is one of the most deadly and prevalent cancers. A routine follow‐up plan for liver cancer is crucial but limited. In the present study, we aimed to disclose possible risk factors and critical survival time windows for primary liver cancer. Methods We enrolled 692 liver cancer patients from Sun Yat‐sen University Cancer Center (SYSUCC). Univariate and multivariate logistic regression analyses of cirrhosis and recurrence were conducted. A meta‐analysis was utilized to validate an indication of creatinine (CRE) in recurrence. Conditional survival analysis was performed using the Kaplan–Meier method. The results were further verified by the SYSUCC validation cohort and Surveillance, Epidemiology, and End Results (SEER) validation cohort. Results Our results indicated that A/G, history of hepatitis, history of alcohol consumption and platelet (PLT) might be potential prognostic factors for cirrhosis in liver cancer patients. CRE was significantly correlated with recurrence due to various therapies, especially after transarterial embolization. Moreover, 1.5 years to 2 years may be a critical time window for deterioration in survival rate based on the conditional survival analysis. Conclusion A/G, history of hepatitis, alcohol consumption and PLT may be potential prognostic factors for cirrhosis in liver cancer patients. More attention should be focused on the renal function when treating the patients due to the significant role of CRE. 1.5 years to 2 years is a critical time window for deterioration in survival rate for liver cancer patients that contributes to determining the optimal follow‐up plan in the future.

Background: Steady evolution of therapies has improved prognosis of patients with multiple myeloma (MM) over the past two decades. Yet, knowledge about survival trends and causes of death in MM might play a crucial role in long-term management of this patient collective. Here, we investigate time trends in myeloma-specific survival at the population level over two decades and analyse causes of death in times of prolonged survival. Methods: Age-standardised and age group-specific relative survival (RS) of MM patients aged < 80 years at diagnosis was estimated for consecutive time periods from 2000–2019 using data from the Cancer Registry of North Rhine-Westphalia in Germany. Conditional RS was estimated for patients who already survived one to five years post diagnosis. Causes of death in MM patients were analysed and compared to the general population using standardised mortality ratios (SMR). Results: Three thousand three hundred thirty-six MM cases were included in the time trend analysis. Over two decades, age-standardised 5-year RS increased from 37 to 62%. Age-specific survival improved from 41% in period 2000–2004 to 69% in period 2015–2019 in the age group 15–69 years, and from 23 to 47% in the age group 70–79 years. Conditional 5-year RS of patients who survived five years after diagnosis slightly improved as compared to unconditional 5-year RS at diagnosis. MM patients are two times more likely to die from non-myeloma malignancies (SMR = 1.97, 95% CI 1.81–2.15) and from cardiovascular diseases (SMR = 2.01, 95% CI 1.86–2.18) than the general population. Conclusions: Prognosis of patients with MM has markedly improved since the year 2000 due to therapeutic advances. Nevertheless, late mortality remains a major concern. As survival improves, second primary malignancies and cardiovascular events deserve increased attention. [ABSTRACT FROM AUTHOR]