Survival Data Research Articles

Cancer survival in sub-Saharan Africa (SURVCAN-3): a population-based study

The Cancer Survival in Africa, Asia, and South America project (SURVCAN-3) of the International Agency for Research on Cancer aims to fill gaps in the availability of population-level cancer survival estimates from countries in these regions. Here, we analysed survival for 18 cancers using data from member registries of the African Cancer Registry Network across 11 countries in sub-Saharan Africa. We included data on patients diagnosed with 18 cancer types between Jan 1, 2005, and Dec 31, 2014, from 13 population-based cancer registries in Cotonou (Benin), Abidjan (CÔte d'Ivoire), Addis Ababa (Ethiopia), Eldoret and Nairobi (Kenya), Bamako (Mali), Mauritius, Namibia, Seychelles, Eastern Cape (South Africa), Kampala (Uganda), and Bulawayo and Harare (Zimbabwe). Patients were followed up until Dec 31, 2018. Patient-level data including cancer topography and morphology, age and date at diagnosis, vital status, and date of death (if applicable) were collected. The follow-up (survival) time was measured from the date of incidence until the date of last contact, the date of death, or until the end of the study, whichever occurred first. We estimated the 1-year, 3-year, and 5-year survival (observed, net, and age-standardised net survival) by sex, cancer type, registry, country, and human development index (HDI). 1-year and 3-year survival data were available for all registries and all cancer sites, whereas availability of 5-year survival data was slightly more variable; thus to provide medium-term survival prospects, we have focused on 3-year survival in the Results section. 10 500 individuals from 13 population-based cancer registries in 11 countries were included in the survival analyses. 9177 (87·4%) of 10 500 cases were morphologically verified. Survival from cancers with a high burden and amenable to prevention was poor: the 3-year age-standardised net survival was 52·3% (95% CI 49·4-55·0) for cervical cancer, 18·1% (11·5-25·9) for liver cancer, and 32·4% (27·5-37·3) for lung cancer. Less than half of the included patients were alive 3 years after a cancer diagnosis for eight cancer types (oral cavity, oesophagus, stomach, larynx, lung, liver, non-Hodgkin lymphoma, and leukaemia). There were differences in survival for some cancers by sex: survival was longer for females with stomach or lung cancer than males with stomach or lung cancer, and longer for males with non-Hodgkin lymphomas than females with non-Hodgkin lymphomas. Survival did not differ by country-level HDI for cancers of the oral cavity, oesophagus, liver, thyroid, and for Hodgkin lymphoma. For cancers for which population-level prevention strategies exist, and with relatively poor prognosis, these estimates highlight the urgent need to upscale population-level prevention activities in sub-Saharan Africa. These data are vital for providing the knowledge base for advocacy to improve access to prevention, diagnosis, and care for patients with cancers in sub-Saharan Africa. Vital Strategies, the Martin-Luther-University Halle-Wittenberg, and the International Agency for Research on Cancer. For the French and Portuguese translations of the abstract see Supplementary Materials section.

Characterizing Adaptive Changes and Patient Survival After 2018 Donor Allocation Restructuring: A UNOS Database Analysis.

We sought to characterize adaptive changes to the revised United Network for Organ Sharing donor heart allocation policy and estimate long-term survival trends for heart transplant (HTx) recipients. Patients listed for HTx between October 17, 2013 and September 30, 2021 were identified from the United Network for Organ Sharing database, and stratified into pre- and postpolicy revision groups. Subanalyses were performed to examine trends in device utilization for extracorporeal membranous oxygenation (ECMO), durable left ventricular assist device (LVAD), intra-aortic balloon pump (IABP), microaxial support (Impella), and no mechanical circulatory support (non-MCS). Survival data post-HTx were fitted to parametric distributions and extrapolated to 5 years. We identified 27,523 HTx waitlist candidates during the study period, most of whom (n = 16,376) were waitlisted in the prepolicy change period. Overall, 19,554 patients underwent HTx during the study period (pre: 12,037 and post: 7517). Listings increased after the policy change for ECMO ( P < 0.01), Impella ( P < 0.01), and IABP ( P < 0.01) patients. Listings for LVAD ( P < 0.01) and non-MCS ( P < 0.01) patients decreased. HTx increased for ECMO ( P < 0.01), Impella ( P < 0.01), and IABP ( P < 0.01) patients after the policy change and decreased for LVAD ( P < 0.01) and non-MCS ( P < 0.01) patients. Waitlist survival increased for the overall ( P < 0.01), ECMO ( P < 0.01), IABP ( P < 0.01), and non-MCS ( P < 0.01) groups. Waitlist survival did not differ for the LVAD ( P = 0.8) and Impella ( P = 0.1) groups. Post-transplant survival decreased for the overall ( P < 0.01), LVAD ( P < 0.01), and non-MCS ( P < 0.01) populations. Allocation policy revisions have contributed to greater utilization of ECMO, Impella, and IABP, decreased utilization of LVADs and non-MCS, increased waitlist survival, and decreased post-HTx survival.

A computational pipeline for identifying gene targets and signalling pathways in cancer cells to improve lymphocyte infiltration and immune checkpoint therapy efficacy

Tumour-infiltrating lymphocytes (TILs) are crucial for effective immune checkpoint blockade (ICB) therapy in solid tumours. However, ∼70% of these tumours exhibit poor lymphocyte infiltration, rendering ICB therapies less effective. We developed a bioinformatics pipeline integrating multiple previously unconsidered factors or datasets, including tumour cell immune-related pathways, copy number variation (CNV), and single tumour cell sequencing data, as well as tumour mRNA-seq data and patient survival data, to identify targets that can potentially improve T cell infiltration and enhance ICB efficacy. Furthermore, we conducted wet-lab experiments and successfully validated one of the top-identified genes. We applied this pipeline in solid tumours of the Cancer Genome Atlas (TCGA) and identified a set of genes in 18 cancer types that might potentially improve lymphocyte infiltration and ICB efficacy, providing a valuable drug target resource to be further explored. Importantly, we experimentally validated SUN1, which had not been linked to T cell infiltration and ICB therapy previously, but was one of the top-identified gene targets among 3 cancer types based on the pipeline, in a mouse colon cancer syngeneic model. We showed that Sun1 KO could significantly enhance antigen presentation, increase T-cell infiltration, and improve anti-PD1 treatment efficacy. Moreover, with a single-cell multiome analysis, we identified subgene regulatory networks (sub-GRNs) showing Stat proteins play important roles in enhancing the immune-related pathways in Sun1-KO cancer cells. This study not only established a computational pipeline for discovering new gene targets and signalling pathways in cancer cells that block T-cell infiltration, but also provided a gene target pool for further exploration in improving lymphocyte infiltration and ICB efficacy in solid tumours. A full list of funding bodies that contributed to this study can be found in the Acknowledgements section.

Breast conservation versus mastectomy for metaplastic breast cancer: A systematic review and meta-analysis.

Metaplastic breast cancer is a rare aggressive subtype of breast cancer for which there are no clear treatment guidelines regarding the optimal surgical approach. This systematic review and meta-analysis aimed to evaluate survival outcomes of patients with metaplastic breast cancer undergoing breast conservation compared with mastectomy. We identified studies from MEDLINE, Pubmed, EMBASE, Google Scholar, the Cochrane Library Register of Controlled Trials and the EBM Reviews Register. Studies were deemed suitable for inclusion where they compared breast-conserving surgery to mastectomy with the primary outcome of overall survival. Survival data were pooled using a random-effects model. From the 456 citations screened by our search, three studies were assessed as eligible for inclusion. There were a total of 2995 patients who underwent mastectomy and 1909 who underwent breast conservation. The median follow-up time was 43 months. Meta-analysis demonstrated no significant difference between breast conservation and mastectomy (pooled HR 0.89, 95% CI, 0.56-1.42, p=0.631). Wide local excision, in conjunction with adjuvant radiation and judicious use of chemotherapy, may be a reasonable alternative to mastectomy as surgical management of metaplastic breast cancer as part of an individualized, multidisciplinary approach.

Comprehensive analysis revealed P4Hs as new biomarkers for prognosis and immunotherapy in head and neck cancer

Prolyl 4-hydroxylases (P4Hs) are a family of key modifying enzymes in collagen synthesis. P4Hs have been confirmed to be closely associated with tumor occurrence and development. However, the expression of P4Hs in head and neck cancer (HNSC) as well as its relationship with prognosis and tumor immunity infiltration has not yet been analyzed. We investigated the transcriptional expression, survival data, and immune infiltration of P4Hs in patients with HNSC from multiple databases. P4H1-3 expression was significantly higher in HNSC tumor tissues than in normal tissues. Moreover, P4HA1 and P4HA2 were associated with tumor stage, patient prognosis, and immune cell infiltration. P4HA3 was related to patient prognosis and immune cell infiltration. Correlation experiments confirmed that P4HA1 may serve as a prognosis biomarker and plays a role in the progression of nasopharyngeal carcinoma. These findings suggest that P4HA1-3 may be a novel biomarker for the prognosis and treatment of HNSC, which is expected to support the development of new therapies for patients with head and neck tumors and improve patient outcomes.

BAYES ESTIMATION OF EXPONENTIALLY DISTRIBUTED SURVIVAL DATA UNDER SYMMETRIC AND ASYMMETRIC LOSS FUNCTIONS

In a research study, population data are often not available, so the population parameter is unknown. Meanwhile, knowledge about the population parameter is needed to know the characteristics of the studied population. Therefore, it is needed to estimate the parameter of the population which can be estimated by sample data. There are several methods of parameter estimation which are generally classified into classical and Bayesian method. This research studied the Bayesian parameter estimation method to determine the parameters of the exponentially distributed survival data associated with the reliability measure of the estimates under symmetric and asymmetric loss functions for complete sample data in a closed form. The symmetric loss functions used in this research are Squared Error Loss Function (SELF) and Minimum Expected Loss Function (MELF). The asymmetric loss functions used are the General Entropy Loss Function (GELF) and Linex Loss Function (LLF). Performance of some loss functions used in this research are then compared through numerical simulation to select the best loss function in determining the parameter estimation of the exponentially distributed survival data. We also studied which loss function is best for underestimation and overestimation modeling. Based on simulation results, the Bayes estimates using MELF is the best method to estimate population parameters of the exponentially distributed survival data for the overestimation modeling, while LLF is the best for the underestimation modeling. We provided direct application in a case study of fluorescence lamp survival data. The results show that the best method to estimate the parameter of the standard fluorescence life data is using LLF for underestimation with and MELF for overestimation with .

Understanding diffuse leptomeningeal glioneuronal tumors.

Diffuse leptomeningeal glioneuronal tumors (DLGNTs) pose a rare and challenging entity within pediatric central nervous system neoplasms. Despite their rarity, DLGNTs exhibit complex clinical presentations and unique molecular characteristics, necessitating a deeper understanding of their diagnostic and therapeutic nuances. This review synthesizes contemporary literature on DLGNT, encompassing epidemiology, clinical manifestations, pathological features, treatment strategies, prognostic markers, and future research directions. To compile the existing body of knowledge on DLGNT, a comprehensive search of relevant databases was conducted. DLGNT primarily affects pediatric populations but can manifest across all age groups. Its diagnosis is confounded by nonspecific clinical presentations and overlapping radiological features with other CNS neoplasms. Magnetic resonance imaging (MRI) serves as a cornerstone for DLGNT diagnosis, revealing characteristic leptomeningeal enhancement and intraparenchymal involvement. Histologically, DLGNT presents with low to moderate cellularity and exhibits molecular alterations in the MAPK/ERK signalling pathway. Optimal management of DLGNT necessitates a multidisciplinary approach encompassing surgical resection, chemotherapy, radiotherapy, and emerging targeted therapies directed against specific genetic alterations. Prognostication remains challenging, with factors such as age at diagnosis, histological subtypes, and genetic alterations influencing disease progression and treatment response. Long-term survival data are limited, underscoring the need for collaborative research efforts. Advancements in molecular profiling, targeted therapies, and international collaborations hold promise for improving DLGNT outcomes. Harnessing the collective expertise of clinicians, researchers, and patient advocates, can advance the field of DLGNT research and optimize patient care paradigms.

Novel prognostic biomarkers in nasopharyngeal carcinoma unveiled by mega-data bioinformatics analysis

Nasopharyngeal carcinoma (NPC) is commonly diagnosed at an advanced stage with a high incidence rate in Southeast Asia and Southeast China. However, the limited availability of NPC patient survival data in public databases has resulted in less rigorous studies examining the prediction of NPC survival through construction of Kaplan-Meier curves. These studies have primarily relied on small samples of NPC patients with progression-free survival (PFS) information or data from head and neck squamous cell carcinoma (HNSCC) studies almost without NPC patients. Thus, we coanalyzed RNA expression profiles in eleven datasets (46 normal (control) vs 160 tumor (NPC)) downloaded from the Gene Expression Omnibus (GEO) database and survival data provided by Jun Ma from Sun Yat-sen University. Then, differential analysis, gene ontology (GO) enrichment, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis and network analysis were performed using STRING database. After that, 2142 upregulated differentially expressed genes (DEGs) and 3857 downregulated DEGs were screened. Twenty-five of them were identified as hub genes, which were enriched in several pathways (cilium movement, extracellular matrix structural constituent, homologous recombination and cell cycle). Utilizing the comprehensive dataset we amassed from GEO database, we conducted a survival analysis of DEGs and subsequently constructed survival models. Seven DEGs (RASGRP2, MOCOS, TTC9, ARHGAP4, DPM3, CD37, and CD72) were identified and closely related to the survival prognosis of NPC. Finally, qRT-PCR, WB and IHC were performed to confirm the elevated expression of RASGRP2 and the decreased expression of TTC9, CD37, DPM3 and ARHGAP4, consistent with the DEG analysis. Conclusively, our findings provide insights into the novel prognostic biomarkers of NPC by mega-data bioinformatics analysis, which suggests that they may serve special targets in the treatment of NPC.

Stereotactic central/core ablative radiation therapy: results of a phase I study of a novel strategy to treat bulky tumor

PurposeBulky tumor remains as a challenge to surgery, chemotherapy and conventional radiation therapy. Hence, in efforts to overcome this challenge, we designed a novel therapeutic paradigm via strategy of Stereotactic Central/Core Ablative Radiation Therapy (SCART).), which is based on the principles of SBRT (stereotactic body radiation therapy and spatially fractionated radiation therapy (SFRT). We intend to safely deliver an ablative dose to the core of the tumor and with a low dose at tumor edge. The purpose of the phase 1 study was to determine dose-limiting toxicities (DLT)s and the Maximum Tolerated Dose (MTD) of SCART.Methods and materialsWe defined a SCART-plan volume inside the tumor, which is proportional to the dimension of tumor. VMAT/Cyberknife technique was adopted. In the current clinical trial; Patients with biopsy proven recurrent or metastatic bulky cancers were enrolled. The five dose levels were 15 Gy X1, 15Gy X3, 18GyX3, 21GyX3 and 24GyX3, while keeping the whole tumor GTV’s border dose at 5Gy each fraction. There was no restriction on concurrent systemic chemotherapy agents.Results21 patients were enrolled and underwent SCART. All 21 patients have eligible data for study follow-up. Radiotherapy was well tolerated with all treatment completed as scheduled. The dose was escalated for two patients to 24GyX3. No grade 3 or higher toxicity was observed in any of the enrolled patients. The average age of patients was 66 years (range: 14–85) and 13 (62%) patients were male. The median SCART dose was 18Gy (range: 15 - 24). Six out of the 18 patients with data for overall survival (OS) died, and the median time to death was 16.3 months (range: 1 - 25.6). The mean percent change for tumor shrinkage between first visit volumes and post-SCART volumes was 49.5% (SD: 40.89, p-value:0.009).ConclusionSCART was safely escalated to 24 GyX 3 fractions, which is the maximum Tolerated Dose (MTD) for SCART. This regimen will be used in future phase II trials.

#2499 Multicenter observational study on the impact of continuous monitoring of vascular access on the survival and quality of life of patients on dialysis

Abstract Background and Aims AVE is a multicenter observational study aimed at evaluating the improvements in dialysis efficiency, AVF longevity and mortality that can be achieved by implementing both monitoring by a multidisciplinary team. The universal goal of AV monitoring is to identify early events such as stenosis and intervene before thrombosis, thus maximizing the longevity of access and minimizing morbidity. Method This study takes advantage of the opportunity to use data from 19 hemodialysis centers and approximately 1000 patients and to correlate and examine variables that are commonly reported with each treatment, trends in AV use, trends in patient characteristics, and the practice associated with VA. The data were collected by nurses in a specific section of the management database at each treatment for 5 years. Results Trends at the beginning and at the end of the study were evaluated, and Kaplan Maier curves were performed regarding the survival of the VA and the survival of the patients. The average age of 1000 patients enrolled was 73.5 years. Native AVF was used by 79%, AVG by 2% and CVC by 19%. With increasing age, the use of CVC goes from 6% (15-39 years) to 50.5% in patients over 85 years old. The most frequent complications were: Thrombosis 16.5%, Infections 5.5%. VA-related hospitalization days are 28.7% of total days. The average dialysis goals achieved were: QB 290 ml/Min; purified blood 69.7 L; KT/V:1.35. The AVE study, the survival curves evaluated in aggregate were not different between men and women during the observation period (year 2018: p = 0.327; year 2019: p = 0.174; year 2020: p = 0.343). This finding was also confirmed when the survival data were analyzed according to gender and chronological age. No difference was observed between genders while the significant difference (p = 0.000) between chronological age levels was confirmed as shown in the Figure Conclusion By interpreting data collection for specific performance measures using accurate reports, healthcare professionals can highlight AV performance/inefficiencies and provide correct information to clinical staff to support them in their daily clinical practice and decision making.

#2487 Deleterious renal outcome in patients with thrombotic microangiopathy after lung transplantation: the lung TMA trial

Abstract Background and Aims Thrombotic microangiopathy (TMA) is a rare but severe complication following lung transplantation. The pathogenesis is poorly understood, involving endothelial damage and various risk factors, including calcineurin inhibitor (CNI) toxicity. We aimed to evaluate diagnostic accuracy, identify risk factors for and assess the renal and overall survival of TMA in this patient group. Method We performed a retrospective study of patients with TMA after lung transplant between 01/01/2000-01/01/2021. Matching controls were selected based on underlying lung disease, age, gender, CMV risk, and immunosuppressive regimen. Overall survival and baseline data (age, gender) were collected for the whole lung transplant group. Results A total of 29 TMA cases (2.9%) were identified out of 1025 lung transplantations. 48% of patients had a complete hematological assessment with Coombs testing as the most frequent (52%) missing test. The median time from transplantation to TMA was 5.9 months. 76% of the episodes occurred before 12 months. 77% of patients had organ damage with acute kidney injury in 72%. At the time of TMA 38% of patients had a cytomegalovirus (CMV) infection. Arterial hypertension was found in 31% and acute rejection in 11%. The immunosuppressive scheme consisted of tacrolimus/mycophenolate mofetil and corticosteroids in the majority of cases (56%). Tacrolimus (n = 22) and cyclosporine (n = 7) trough levels were respectively 11.8 and 207 µg/l at the time of TMA. Treatment consisted of change in immunosuppressive regimen (72%), 31% received plasmapheresis. When comparing the TMA patients with the control group a higher rate of donor specific antibodies were found (11% vs 1%), a lower median time till chronic lung allograft dysfunction (37 m vs 91 m) and a higher prevalence of end-stage renal disease (24% vs 6%) and overall death (97% vs 44%) with mortality being significantly higher (p &amp;lt; 0.01). Fig. 1 illustrates the overall outcome. Conclusion This study illustrates the clinical characteristics and outcomes of TMA after lung transplantation. Even though the prevalence is low the effects are deleterious with acute kidney injury in the majority of cases and higher risk of end-stage renal disease and mortality. Our study emphasizes the need for higher further research into risk factors, and therapeutic strategies to prevent and improve patient outcomes. Furthermore, the findings underscore the importance of vigilant monitoring and tailored interventions for TMA in lung transplant patients.

#1466 Age- and kidney function-dependent life expectancy of patients after COVID-19

Abstract Background and Aims The life expectancy among survivors of SARS-CoV-2 infection may be influenced by age, pre-existing health conditions, and the severity of the initial infection. This study aimed to investigate the life expectancy in patients that survived the acute phase of COVID-19 and the association with kidney function. Method Survival data of 649 unvaccinated patients from our previous study “Prospective Validation of a Proteomic Urine Test for Early and Accurate Prognosis of Critical Course Complications in Patients with SARS-CoV-2 Infection” (CRIT-COV-U) [1] was collected until December 2023 in six different countries. These patients had been recruited within the first and second wave in 2020-2021 (mostly infected with wild-type virus) and had survived the acute phase of COVID-19 (CritCov-U study period 21 days after infection). The age dependent death rate in this cohort was compared to age- and sex-matched data of non-SARS-CoV-2 infected patients (n = 5192) extracted from human urinary database. The association of chronic kidney disease biomarker CKD273 with mortality was investigated in both cohorts using Kaplan-Meier analysis. Cox-regression analysis was used to assess variables associated with mortality in the COVID-19 population. Results Mortality was age dependent in both cohorts and markedly higher in patients who had survived the acute phase of COVID-19 in comparison to non-infected individuals (Fig. A-E). Within the first year after infection, mortality was up to 16.5 times higher in patients younger than 50 years in comparison to non-infected controls. Kidney status estimated by the CKD273 score was associated with a poor outcome in both COVID-19 patients and age- and sex-matched controls, respectively (Fig. F-G). The hazard ratio (HR) for mortality during the first year of follow-up for patients with the highest CKD273 score was 12.7, a huge increase in comparison to HR = 6.6 in the matched control group. In the Cox-regression model, CKD273 significantly contributed to death prediction, next to age and COVID-19 severity score at baseline. Conclusion SARS-CoV-2 infection during the first and second wave increased the risk of mortality in the follow-up period beyond the acute phase of the first 21 days. Kidney function appears to be a key element in the underlying molecular pathology of this process, indicating the importance of kidney-protective measures. Of note, among those who survived the acute phase of COVID-19, increase in mortality within the first year after infection compared to a non-infected control group was highest in the younger individuals.

Risk factors, histopathological landscape, biomarkers, treatment patterns and survival of early-onset colorectal cancer: A narrative review.

Early-onset colorectal cancer (EOCRC) incidence has increased in most Western countries over the last decade, with Australia at the forefront. Recent literature has thus focused on characterizing EOCRC from later-onset colorectal cancer (LOCRC). Earlier exposure to modifiable risk factors resulting in gut dysbiosis has been linked with EOCRC development. EOCRCs have more aggressive histopathological features with somatic mutations resulting in pro-inflammatory tumor microenvironments. There is a tendency to treat EOCRCs with multimodal chemotherapeutic regimens and more extensive surgery than LOCRCs with conflicting postoperative outcomes and survival data. Current research is limited by a lack of Australasian studies, retrospective study designs, and heterogeneous definitions of EOCRC. Future research should address these and focus on investigating the role of immunotherapies, establishing minimally invasive diagnostic biomarkers and nomograms, and evaluating the survival and functional outcomes of EOCRC.

Comparative efficacy of six programmed cell death Protein-1 inhibitors as first-line treatment for advanced non-small cell lung cancer: a multicenter retrospective cohort study

The purpose of this study was to assess the comparative efficacy of six programmed cell death-1 inhibitors (nivolumab, pembrolizumab, sintilimab, tislelizumab, toripalimab, and camrelizumab) that have been used as first-line therapy for Chinese patients with advanced non-small cell lung cancer (NSCLC), which remains unclear. We determined the differences in efficacy by observing patient survival data, with the goal of informing future treatment options. Retrospective data analysis from June 2015 to April 2023 included 913 patients across six groups: nivolumab (123%, 13.5%), pembrolizumab (421%, 46.1%), sintilimab (239%, 26.1%), tislelizumab (64%, 7.0%), toripalimab (39%, 4.3%), and camrelizumab (27%, 3.0%). The median progression-free survival (PFS) for each group was 16.0, 16.1, 18.4, 16.9, 23.7, and 12.8 months, and the median overall survival (OS) was 33.7, 36.1, 32.5, not reached, 30.9 and 46.0 months for the nivolumab, sintilimab, pembrolizumab, tislelizumab, toripalimab, and camrelizumab groups, respectively. While differences existed in the objective response rates among groups (p &amp;lt; 0.05), there were no significant differences (all p &amp;gt; 0.05) in PFS or OS. The findings suggest comparable efficacy among these PD-1 inhibitors for NSCLC treatment, underscoring their collective suitability and aiding treatment decisions.

Economic aspects of long-term left ventricular assist device treatment for chronic heart failure.

Technological advances and the current shortage of donor organs have contributed to an increase in the number of left ventricular assist device (LVAD) implantations in patients with end-stage heart failure. Demographic change and medical progress might raise the number of these patients, resulting in a further increase in the number of LVAD implantations. The aim of this study was to evaluate the long-term costs of LVAD therapy and identify diagnoses resulting in expensive stays. In this retrospective analysis of prospectively collected data, all patients after implantation of a second- or third-generation LVAD by 31 March 2022 were included. In addition to demographic and survival data, revenues and case mix points were determined for each patient. Of the 163 patients included, 75.5% were male. The mean age at LVAD implantation was 52±14years. The mean survival was 1458±127days. During follow-up, the total inpatient treatment time per patient was 70±87days. The average duration of outpatient treatment was 55.1%, based on the total duration of support. The average revenue per patient for the implant stay was $193192.35±$111801.29, for inpatient readmissions $52068.96±$116630.00, and for outpatient care $53195.94±$62363.53. LVAD implantation in patients with end-stage heart failure leads to improved survival but a significant increase in treatment costs. Further multi-centre studies are necessary in order to be able to assess the effects of long-term LVAD treatment on the healthcare system.

A metric for comparison and visualization of age disparities in cancer survival.

Diagnostic age is an important determinant of cancer survival but the methods generally used to analyze age-group-specific survival are not developed for ready visualization of survival differences. We aim at developing a novel metric for comparing and visualizing age-group-specific survival data over different cancers, sexes, periods and countries. The metric describes the mean absolute deviation between age-groups. The metric can be used in two variations, one showing the mean variation and its 95% confidence intervals and the other highlighting individually each age-groups distinguishing positive or negative deviations. We demonstrate the applications with age-group- specific 5-year relative survival data from the NORDCAN database RESULTS: The mean absolute deviation between age-groups for Swedish colon cancer survival declined from about 5% in 1972-1981-1% in 1992-2001 and to 1.3% in 2012-2021. Patients diagnosed before age 50 years accounted for the largest positive deviation. For acute myeloid leukemia (AML) the mean deviation increased from 4% (female) to 17% and 23%. Patients diagnosed at age below 50 years showed the largest deviations. Comparing colon cancer mean deviations between the Nordic countries, a time-related decline was observed for all, those in Sweden ending at the lowest and in Finland the highest level. We demonstrated the usefulness of the devised metric for summarizing age-specific survival data between cancers, sexes, periods and countries. The two variations of the metric allow a simple visual presentation of the survival experience as to deviation of the survival data, its 95%CIs and its highlighted individual age-group components.

Z-residual diagnostic tool for assessing covariate functional form in shared frailty models

ABSTRACT Survival analysis often involves modeling hazard functions while considering frailty to account for unobserved cluster-level factors in clustered survival data. Shared frailty models have gained popularity for this purpose, but assessing covariate functional form in these models presents unique challenges. Martingale and deviance residuals are commonly used for visually assessing covariate functional form against continuous covariates. Nevertheless, their subjective nature and lack of a reference distribution make it challenging to derive numerical statistical tests from these residuals. To address these limitations, we propose ‘Z-residuals’, a novel diagnostic tool designed for shared frailty models, leveraging the concept of randomized survival probability and introducing both graphical and numerical tests. To implement this approach, we develop an R package to compute Z-residuals for shared frailty models. Through extensive simulation studies, we demonstrate the high power of our derived numerical test for assessing the functional form of covariates. To validate the effectiveness of our method, we apply it to a real data application concerning the modelling of survival time for acute myeloid leukemia patients. Our Z-residual diagnosis results reveal the inadequacy of log-transformation of the covariate, highlighting the limitations of other diagnostic methods for effectively assessing covariate functional form in shared frailty models.

HEART FAILURE PATIENTS WITH IMPROVED EJECTION FRACTION: INSIGHTS FROM THE MECKI SCORE DATABASE

Abstract Aims Improvement of left ventricular ejection fraction is a major goal of heart failure (HF) treatment. However, data on clinical characteristics, exercise performance and prognosis in HF patients who improved ejection fraction (HFimpEF) are scarce. The study aimed to determine whether HFimpEF patients have a distinct clinical phenotype, biology and prognosis than HF patients with persistently reduced ejection fraction (pHFrEF). Methods 7948 patients enrolled in the Metabolic Exercise Cardiac Kidney Indexes (MECKI) score database were evaluated (median follow–up of 1490 days). We analyzed clinical, laboratory, ECG, echocardiographic, exercise, and survival data from HFimpEF (n=1504) and pHFrEF (n=6017) patients. The primary endpoint of the study was the composite of cardiovascular death, left ventricular assist device implantation, and urgent heart transplantation. Results Main results are shown in Figure 1. HFimpEF patients had lower HF severity: LVEF 44.0[41.0–47.0] vs. 29.7[24.1–34.5]%, BNP 122[65–296] vs. 373[152–888] pg/mL, hemoglobin 13.5[12.2–14.6] vs. 13.7[12.5–14.7] g/dL, renal function by MDRD 72.0[56.7– 89.3] vs. 70.4[54.5–85.3] mL/min, peakVO2 62.2[50.7–74.1] vs. 52.6[41.8–64.3]%pred, VE/VCO2 slope 30.0[26.9–34.4] vs. 32.1[28.0–38.0] in HFimpEF and pHFrEF, respectively (p&amp;lt;0.001 for all). Cardiovascular mortality rates were 26.6 and 46.9 per 1000 person–years for HFimpEF and pHFrEF, respectively (p&amp;lt;0.001). Kaplan–Meier analysis (Fig.2) showed that HFimpEF had better a long–term prognosis compared with pHFrEF patients. After adjustment for variables differentiating HFimpEF from pHFrEF, except echocardiographic parameters, the Kaplan–Meier curves showed the same prognosis. Conclusions HFimpEF represents a peculiar group of HF patients whose clinical, laboratory, ECG, echocardiographic, and exercise characteristics parallel the recovery of systolic function. Nonetheless, these patients remain at risk for adverse outcome.

Insulin resistance, coronary artery lesion complexity and adverse cardiovascular outcomes in patients with acute coronary syndrome

BackgroundInsulin resistance (IR) is linked to both the complexity of coronary artery lesions and the prognosis of acute coronary syndrome (ACS). However, the precise extent of this correlation and its impact on adverse cardiovascular outcomes in ACS patients remain unclear. Therefore, this study aims to investigate the intricate relationship between IR, coronary artery lesion complexity, and the prognosis of ACS through a cohort design analysis.MethodA total of 986 patients with ACS who underwent percutaneous coronary intervention (PCI) were included in this analysis. IR was assessed using the triglyceride-glucose (TyG) index, while coronary artery lesion complexity was evaluated using the SYNTAX score. Pearson’s correlation coefficients were utilized to analyze the correlations between variables. The association of the TyG index and SYNTAX score with major adverse cardiovascular events (MACEs) in ACS was investigated using the Kaplan-Meier method, restricted cubic splines (RCS), and adjusted Cox regression. Additionally, a novel 2-stage regression method for survival data was employed in mediation analysis to explore the mediating impact of the SYNTAX score on the association between the TyG index and adverse cardiovascular outcomes, including MACEs and unplanned revascularization.ResultsDuring a median follow-up of 30.72 months, 167 cases of MACEs were documented, including 66 all-cause deaths (6.69%), 26 nonfatal myocardial infarctions (MIs) (2.64%), and 99 unplanned revascularizations (10.04%). The incidence of MACEs, all-cause death, and unplanned revascularization increased with elevated TyG index and SYNTAX score. Both the TyG index (non-linear, P = 0.119) and SYNTAX score (non-linear, P = 0.004) displayed a positive dose-response relationship with MACEs, as illustrated by the RCS curve. Following adjustment for multiple factors, both the TyG index and SYNTAX score emerged as significant predictors of MACEs across the total population and various subgroups. Mediation analysis indicated that the SYNTAX score mediated 25.03%, 18.00%, 14.93%, and 11.53% of the correlation between the TyG index and MACEs in different adjusted models, respectively. Similar mediating effects were observed when endpoint was defined as unplanned revascularization.ConclusionElevated baseline TyG index and SYNTAX score were associated with a higher risk of MACEs in ACS. Furthermore, the SYNTAX score partially mediated the relationship between the TyG index and adverse cardiovascular outcomes.

Non-proportional hazards model with a PVF frailty term: application with a melanoma dataset

Survival data analysis often uses the Cox proportional hazards (PH) model. This model is widely applied due to its straightforward interpretation of the hazard ratio under the assumption that the hazard rates for two subjects remain constant over time. However, in several randomized clinical trials with long-term survival data comparing two new treatments, it is frequently observed that Kaplan-Meier plots exhibit crossing survival curves. This violation of the PH assumption of the Cox PH model can not be applied to evaluate the treatment's effect on survival. This paper introduces a novel long-term survival model with non-PH that incorporates a frailty term into the hazard function. This model allows us to examine the effect of prognostic factors on survival and quantify the degree of unobservable heterogeneity. The model parameters are estimated using the maximum likelihood estimation procedure, and we evaluate the performance of the proposed models through simulation studies. Additionally, we demonstrate the applicability of our approach by fitting the models to a real skin cancer dataset.