Estimate Survival Probabilities Research Articles

CT-163 Outcomes of Hematological Malignancy Patients Who Underwent Haploidentical SC Transplant With ATG of 2 Mg/kg Based Conditioning Regimen

Hematopoietic stem cell transplantation from human leukocyte antigen (HLA)-haploidentical family members (Haplo-HSCT) offers a potential cure for patients with hematological malignancies who lack an HLA-matched donor. Haplo-HSCT with post-transplant cyclophosphamide (PTCY) is associated with induced immune tolerance, rapid hematopoietic recovery, lower graft-versus-host disease (GVHD), and lower non-relapse mortality (NRM). We noticed a high incidence of high-grade GVHD, so we added antithymocyte globulin (ATG) to the Haplo-HSCT transplant platform. Here we review the outcomes of patients who received PTCY and ATG 2 mg/kg (ATG-2). We retrospectively reviewed the medical records of all patients who underwent Haplo-HSCT for malignant hematologic disorders, using myeloablation, ATG-2, and PTCY for GVHD prophylaxis. We analyzed the patient's characteristics and outcomes of the transplant. We used the Kaplan-Meier method to estimate survival probabilities. Statistical analysis was performed with EasyMedStat. Fifty-three-patients were reviewed, 26 (49.1%) males and 27 (50.9%) Females. The majority of patients had AML (60%). Other diagnoses included ALL, CML, MDS, APL, and BPDCN. Seventy-one percent of patients received bone marrow harvested cells and 27% received PBSCT and 2% received both BM and PBSCT. The conditioning was myeloablative in the form of Thiotepa/Busulfan/Fludarabine (73.5%) for myeloid malignancies and Fludarabine/TBI 1000 cGy (26.4%) for lymphoid malignancies. The median duration of follow-up was 15 months. At 12 months, the overall survival (OS) was 73.4% (95% CI: 59.3-83.3), and the relapse-free survival (RFS) was 70.3% (95% CI: 55.6-80.9). 33% of patients developed GII to IV acute GVHD and 17% of patients developed extensive chronic GVHD. There were no cases of primary graft failure (GF), but two patients developed secondary GF. One-third of patients developed hemorrhagic cystitis (33.9%) and the majority of patients (90.5%) developed CMV reactivation. Only two patients developed Veno-occlusive disease (VOD). Haplo-HSCT for hematological malignancies with myeloablative conditioning, PTCY and ATG 2 mg/kg is feasible and associated with favorable OS, and RFS. The risk of GVHD, VOD, and GF is comparable to other case series.

Spatial and temporal parasite dynamics: microhabitat preferences and infection progression of two co-infecting gyrodactylids

BackgroundMathematical modelling of host-parasite systems has seen tremendous developments and broad applications in theoretical and applied ecology. The current study focuses on the infection dynamics of a gyrodactylid-fish system. Previous experimental studies have explored the infrapopulation dynamics of co-infecting ectoparasites, Gyrodactylus turnbulli and G. bullatarudis, on their fish host, Poecilia reticulata, but questions remain about parasite microhabitat preferences, host survival and parasite virulence over time. Here, we use more advanced statistics and a sophisticated mathematical model to investigate these questions based on empirical data to add to our understanding of this gyrodactylid-fish system.MethodsA rank-based multivariate Kruskal-Wallis test coupled with its post-hoc tests and graphical summaries were used to investigate the spatial and temporal parasite distribution of different gyrodactylid strains across different host populations. By adapting a multi-state Markov model that extends the standard survival models, we improved previous estimates of survival probabilities. Finally, we quantified parasite virulence of three different strains as a function of host mortality and recovery across different fish stocks and sexes.ResultsWe confirmed that the captive-bred G. turnbulli and wild G. bullatarudis strains preferred the caudal and rostral regions respectively across different fish stocks; however, the wild G. turnbulli strain changed microhabitat preference over time, indicating microhabitat preference of gyrodactylids is host and time dependent. The average time of host infection before recovery or death was between 6 and 14 days. For this gyrodactylid-fish system, a longer period of host infection led to a higher chance of host recovery. Parasite-related mortalities are host, sex and time dependent, whereas fish size is confirmed to be the key determinant of host recovery.ConclusionFrom existing empirical data, we provided new insights into the gyrodactylid-fish system. This study could inform the modelling of other host-parasite interactions where the entire infection history of the host is of interest by adapting multi-state Markov models. Such models are under-utilised in parasitological studies and could be expanded to estimate relevant epidemiological traits concerning parasite virulence and host survival.Graphical

Construction and Validation of a CNV-Driven Ferroptosis-Related Gene Signature for Predicting the Prognosis of Lung Adenocarcinoma

Background. Previous studies have shown that ferroptosis plays an integral role in the development of cancer and copy number variations (CNVs) have been reported to associated with the ferroptosis. However, the role of CNVs-driven ferroptosis-related genes (FRGs) in lung adenocarcinoma (LUAD) continues to be poorly understood. Therefore, we aimed to establish a novel gene signature in LUAD based on CNVs-driven ferroptosis-related genes. Methods. The transcriptome data and clinical features of LUAD patients were downloaded from the Gene Expression Omnibus (GEO) database and The Cancer Genome Atlas (TCGA) database. Differential analysis was carried out to recognize differentially expressed CNV-driven FRGs. Univariate Cox and least absolute shrinkage and selection operator (LASSO) regression analyses were utilized to identify prognosis-associated genes. Kaplan-Meier (K-M) analysis was a builder to estimate the worth of model. In addition, the nomogram was created to estimate survival probability of each patient. Ultimately, the immune microenvironment landscape between high and low risk groups was evaluated. Results. A total of 22 differentially expressed CNV-driven FRGs were acquired in LUAD. These genes were significantly associated with serine family amino acid metabolism, iron regulation, reactive oxygen species metabolism, and cellular response to oxidative stress, and were involved in amino acid metabolism, malaria, amino acid biosynthesis, and HIF-1 signaling pathways. Moreover, on the strength of 6 genes (TFAP2A, SLC2A1, AURKA, CDO1, SLC7A11, and ALOX5), the prognostic model was created, and the LUAD samples were significantly fall into the high- and low-risk groups, with the high-risk group had a poorer prognosis. Furthermore, risk score was an independent prognostic element. The nomogram with excellent predictive performance was developed for calculating the final result of LUAD patients at 1, 2, and 3 years. Finally, 19 immune cells had different infiltration differences among groups. Conclusion. A novel CNV-driven ferroptosis-related prognosis was established and could be used as a predictive indicator in LUAD. However, further clinical and in vivo in vitro experiments are necessary.

Survival of primary liver cancer for people from culturally and linguistically diverse backgrounds in Australia

BackgroundSurvival for Primary Liver Cancer (PLC) has been investigated in Australia, but limited work has been conducted on the burden for people with different socioeconomic status, region of residence, causes of PLC, and culturally and linguistically diverse (CALD) backgrounds. This study aimed to cover this gap in the literature by investigating PLC survival with the aforementioned factors. MethodsThis study linked four administrative datasets: Victorian Cancer Registry, Admitted Episodes Dataset, Emergency Minimum Dataset, and Death Index. The cohort was all cases with a PLC notification within the Victorian Cancer Registry between 01/01/2008 and 01/01/2016. The Kaplan-Meier method was used to estimate survival probabilities and the log-rank test was used to compare the difference in survival between subgroups. The Cox proportional hazard model was used to explore factors associated with PLC survival. ResultsThe 1-, 3- and 5-year survival rates were 50.0%, 28.1% and 20.6%, respectively, with a median survival of 12.0 months (95% confidence interval (CI): 11.0 – 12.9 months). Higher survival was associated with younger age, hepatocellular carcinoma, and higher socio-economic status. People born in Asian, African, and American regions had higher survival than those born in Australia and New Zealand. Cases with viral hepatitis as an identified aetiology had higher survival than those whose PLC was related to alcohol consumption (hazard ratio=1.52, 95% CI: 1.19 – 1.96), diabetes and fatty liver disease (hazard ratio=1.35, 95% CI: 1.08 – 1.68). ConclusionSurvival outcomes for people diagnosed with PLC were still poor and affected by many factors. Asian and African cases had better survival than Australian and New Zealand patients as PLC in Asian and African cases was mostly caused by viral hepatitis. Metropolitan areas were associated with a higher survival than rural areas, not only due to accessibility to surveillance and healthcare services but also because the majority of overseas-born patients reside in metropolitan areas.

Investigation of simultaneous variation of surface diffuseness and central depression in the estimation of absorption effects

In this paper, we investigate the effect of simultaneous variation of surface diffuseness and central depression, in case of model-dependent Fermi matter density distributions, on the estimation of survival probability, Coulomb excitation cross-section and absorption effects for [Formula: see text] Au system. Further, the role of model-dependent Fermi matter density distribution and model independent [Formula: see text] matter density distribution has also been investigated in the estimation of the above-mentioned quantities. The simultaneous variation of the parameters of the model-dependent density distribution and choice of the density distribution are found to be affecting all the above-mentioned quantities significantly and hence plays a crucial role in the analysis of the Coulomb excitation experiments also.

Standardised survival probabilities: a useful and informative tool for reporting regression models for survival data

BackgroundWhen interested in studying the effect of a treatment (or other exposure) on a time-to-event outcome, the most popular approach is to estimate survival probabilities using the Kaplan–Meier estimator. In the presence of confounding, regression models are fitted, and results are often summarised as hazard ratios. However, despite their broad use, hazard ratios are frequently misinterpreted as relative risks instead of relative rates.MethodsWe discuss measures for summarising the analysis from a regression model that overcome some of the limitations associated with hazard ratios. Such measures are the standardised survival probabilities for treated and untreated: survival probabilities if everyone in the population received treatment and if everyone did not. The difference between treatment arms can be calculated to provide a measure for the treatment effect.ResultsUsing publicly available data on breast cancer, we demonstrated the usefulness of standardised survival probabilities for comparing the experience between treated and untreated after adjusting for confounding. We also showed that additional important research questions can be addressed by standardising among subgroups of the total population.DiscussionStandardised survival probabilities are a useful way to report the treatment effect while adjusting for confounding and have an informative interpretation in terms of risk.

Turnover intention and retention of newly licensed nurses in their first job: A longitudinal study.

To examine newly licensed nurses' retention in their first job and factors related to their turnover. Newly licensed nurses have a high turnover rate within three years of entering their first job. The factors affecting newly licensed nurses' turnover should be identified and prevented. This longitudinal study tracked newly licensed nurses for three years. Data were collected online, and nurses could participate four times in the survey. The Kaplan-Meier method was used to estimate survival curves and to present nurses' retention. Cox proportional hazards regression model was used to analyze factors related to turnover. The estimated survival probabilities in nurses' first job at one, two, and three years were 0.927, 0.778, and 0.686, respectively. Nurses who reported turnover intention within one year in the first survey had significantly lower survival probabilities than those who did not have turnover intention. Turnover was more likely among male nurses. Turnover intention was associated with a significant increased likelihood of nurses leaving their first job. More than one third of newly licensed nurses left their first job within three years of employment. To reduce nurses' turnover, it is necessary to understand and manage turnover intention in advance. Specific steps should be taken to address male nurses' turnover. Turnover intention was the most powerful predictor of turnover. Further research should investigate reasons for turnover intention at the beginning of employment, and strategies to prevent turnover should be developed before nurses enter the workforce. Newly licensed nurses with turnover intention at the beginning of their career should receive particular attention, and wellness programs should be prepared to promote retention.

Synthesizing studies for comparing different treatment sequences in clinical trials.

With advances in cancer treatments and improved patient survival, more patients may go through multiple lines of treatment. It is of clinical importance to choose a sequence of effective treatments (eg, lines of treatment) for individual patients with the goal of optimizing their long-term clinical outcome (eg, survival). Several important issues arise in cancer studies. First, cancer clinical trials are usually conducted by each line of treatment. For a treatment sequence, we may have first line and second line treatment data from two different studies. Second, there is typically a treatment initiation period varying from patient to patient between progression of disease and the start of the second line treatment due to administrative reasons. Additionally, the choice of the second line treatment for patients with progression of disease may depend on their characteristics. We address all these issues and develop semiparametric methods under the potential outcome framework for the estimation of the overall survival probability for a treatment sequence and for comparing different treatment sequences. We establish the large sample properties of the proposed inferential procedures. Simulation studies and an application to a colorectal clinical trial are provided.

Machine Learning for Bankruptcy Prediction in the American Stock Market: Dataset and Benchmarks

Predicting corporate bankruptcy is one of the fundamental tasks in credit risk assessment. In particular, since the 2007/2008 financial crisis, it has become a priority for most financial institutions, practitioners, and academics. The recent advancements in machine learning (ML) enabled the development of several models for bankruptcy prediction. The most challenging aspect of this task is dealing with the class imbalance due to the rarity of bankruptcy events in the real economy. Furthermore, a fair comparison in the literature is difficult to make because bankruptcy datasets are not publicly available and because studies often restrict their datasets to specific economic sectors and markets and/or time periods. In this work, we investigated the design and the application of different ML models to two different tasks related to default events: (a) estimating survival probabilities over time; (b) default prediction using time-series accounting data with different lengths. The entire dataset used for the experiments has been made available to the scientific community for further research and benchmarking purposes. The dataset pertains to 8262 different public companies listed on the American stock market between 1999 and 2018. Finally, in light of the results obtained, we critically discuss the most interesting metrics as proposed benchmarks for future studies.

A flexible Bayesian approach for estimating survival probabilities from age-at-harvest data

A flexible Bayesian approach for estimating survival probabilities from age-at-harvest data

A flexible Bayesian approach for estimating survival probabilities from age-at-harvest data

A flexible Bayesian approach for estimating survival probabilities from age-at-harvest data

A flexible Bayesian approach for estimating survival probabilities from age-at-harvest data

A flexible Bayesian approach for estimating survival probabilities from age-at-harvest data

A flexible Bayesian approach for estimating survival probabilities from age-at-harvest data

A flexible Bayesian approach for estimating survival probabilities from age-at-harvest data

A flexible Bayesian approach for estimating survival probabilities from age-at-harvest data

A flexible Bayesian approach for estimating survival probabilities from age-at-harvest data

Survival and predictors of mortality among HIV-positive children on antiretroviral therapy in public hospitals

BackgroundHuman immunodeficiency virus and acquired immunodeficiency syndrome had created enormous challenges worldwide, and continues to be the world’s serious health and development challenges. Globally, at the end 2017, there were 1.8 million children (< 15 years) living with HIV. The survival of HIV-positive children treated with ART depends on a variety of factors, which might vary greatly with economic, socio-demographic, behavioral risk, and health factors. This study aimed to assess survival status and predictors of mortality among HIV-positive children on antiretroviral therapy at East Gojjam Zone Public hospitals, Northwest Ethiopia.MethodsAn institution-based retrospective cohort study was conducted in selected hospitals of the East Gojjam zone, Northwest Ethiopia, among < 15-year-old children who were newly enrolled in HIV care clinic from January 1st, 2014 to December 31, 2018. Data were collected from patient charts from March 1 to 22, 2019 using a standardized checklist. Data were analyzed by SPSS version 24. A Kaplan–Meier curve and log-rank test were used to estimate the survival time and compare survival curves between variables. Multivariable Cox proportional-hazards model was fitted to identify predictors of survival status taking p-value < 0.05 as statistically significant.ResultIn this study, a total of 251 HIV-positive children on ART were followed up for a total of 60 months, with a mean survival time of 55.54 (± 0.83) (95% CI: 53.90–57.17) months. The overall mortality incidence rate in the cohort during the 626 Child-Year-Observation (CYO) was 2.56/100 CYO. The overall estimated survival probability after starting ART was 0.90 at 60 months of follow-up. In this study age < 5 years, Hgb < 10 gm/dl, CD4 count below threshold, cotrimoxazole preventive therapy, and subnormal weight for height were statistically significant predictors of survival status (P < 0.05).Conclusion and recommendationAge, hemoglobin level, CD4 count, weight for height, and not taking cotrimoxazole preventive therapy were independent predictors of mortality. Therefore, concerned stakeholders should focus on the above-mentioned predictors of mortality and nutritional interventions to enhance the survival of HIV-infected children on antiretroviral therapy.

Estimating survival probabilities of Cambridge Bay Arctic char using acoustic telemetry data and Bayesian multistate capture–recapture models

Arctic fishes are threatened by climatic change and other anthropogenic stressors, yet information on how such changes impact survival remains scarce. Acoustic telemetry has become valuable for studying aspects of fish ecology, including survival, which is invaluable in understanding potential responses to changing conditions. In Cambridge Bay, NU, we have been using acoustic telemetry to study movements and habitat use of the culturally and commercially important Arctic char ( Salvelinus alpinus). Here, we combine acoustic telemetry data and Bayesian multistate mark–recapture models to study the survival of Arctic char from 2014 to 2018 in the region in freshwater and marine/estuarine habitats. We found that survival probabilities were high (&gt;0.87) and models considering two environments (freshwater and marine) perform better than those considering three (including estuarine habitats). Furthermore, the survival in fresh water was higher than survival in marine/estuary environments. Overall, the results of this study further our understanding of important demographic parameters (i.e., survival) for Arctic char in the region, which will be useful in refining fishery management plans for the largest commercial fishery for this species in Canada.

How long do regional MICE events survive? the case of Busan, Korea

ABSTRACT The study examines survival times of regional meeting, incentive, convention, and exhibition (MICE) events by estimating hazard rates over time. Additionally, crucial factors for sustaining MICE events are investigated. This study utilized an innovative analytic technique—survival analysis. To estimate survival probability, 205 MICE events hosted in Busan, South Korea were collected. The survival analysis results showed the most important period for MICE-event survival is the first three years. Cox regression indicated local government support plays an important role in sustaining MICE events. However, four MICE-event themes related to main regional strategic industries had no effect on MICE-event survival.

American Indian/Alaska Native and black colon cancer patients have poorer cause-specific survival based on disease stage and anatomic site of diagnosis

ObjectivesStudies of race-specific colon cancer (CC) survival differences between right- vs. left-sided CC typically focus on Black and White persons and often consider all CC stages as one group. To more completely examine potential racial and ethnic disparities in side- and stage-specific survival, we evaluated 5-year CC cause-specific survival probabilities for five racial/ethnic groups by anatomic site (right or left colon) and stage (local, regional, distant). MethodsWe obtained cause-specific survival probability estimates from National Cancer Institute’s population-based Surveillance, Epidemiology, and End Results (SEER) for CC patients grouped by five racial/ethnic groups (Non-Hispanic American Indian/Alaska Native [AIAN], Non-Hispanic Asian/Pacific Islander [API], Hispanic, Non-Hispanic Black [NHB], and Non-Hispanic White [NHW]), anatomic site, stage, and other patient and SEER registry characteristics. We used meta-regression approaches to identify factors that explained differences in cause-specific survival. ResultsDiagnoses of distant-stage CC were more common among NHB and AIAN persons (>22 %) than among NHW and API persons (< 20 %). Large disparities in anatomic site-specific survival were not apparent. Those with right-sided distant-stage CC had a one-year cause-specific survival probability that was 16.4 % points lower (99 % CI: 12.2–20.6) than those with left-sided distant-stage CC; this difference decreased over follow-up. Cause-specific survival probabilities were highest for API, and lowest for NHB, persons, though these differences varied substantially by stage at diagnosis. AIAN persons with localized-stage CC, and NHB persons with regional- and distant-stage CC, had significantly lower survival probabilities across follow-up. ConclusionsThere are differences in CC presentation according to anatomic site and disease stage among patients of distinct racial and ethnic backgrounds. This, coupled with the reality that there are persistent survival disparities, with NHB and AIAN persons experiencing worse prognosis, suggests that there are social or structural determinants of these disparities. Further research is needed to confirm whether these CC cause-specific survival disparities are due to differences in risk factors, screening patterns, cancer treatment, or surveillance, in order to overcome the existing differences in outcome.

Socioeconomic environment and survival in patients after ST-segment elevation myocardial infarction (STEMI): a longitudinal study for the City of Vienna

ObjectivesThis study investigates the relationship between socioeconomic environment (SEE) and survival after ST-segment elevation myocardial infarction (STEMI) separately for women and men in the City of Vienna, Austria.DesignHospital-based observational data...

DNA methylation changes in response to neoadjuvant chemotherapy are associated with breast cancer survival

BackgroundLocally advanced breast cancer is a heterogeneous disease with respect to response to neoadjuvant chemotherapy (NACT) and survival. It is currently not possible to accurately predict who will benefit from the specific types of NACT. DNA methylation is an epigenetic mechanism known to play an important role in regulating gene expression and may serve as a biomarker for treatment response and survival. We investigated the potential role of DNA methylation as a prognostic marker for long-term survival (> 5 years) after NACT in breast cancer.MethodsDNA methylation profiles of pre-treatment (n = 55) and post-treatment (n = 75) biopsies from 83 women with locally advanced breast cancer were investigated using the Illumina HumanMethylation450 BeadChip. The patients received neoadjuvant treatment with epirubicin and/or paclitaxel. Linear mixed models were used to associate DNA methylation to treatment response and survival based on clinical response to NACT (partial response or stable disease) and 5-year survival, respectively. LASSO regression was performed to identify a risk score based on the statistically significant methylation sites and Kaplan–Meier curve analysis was used to estimate survival probabilities using ten years of survival follow-up data. The risk score developed in our discovery cohort was validated in an independent validation cohort consisting of paired pre-treatment and post-treatment biopsies from 85 women with locally advanced breast cancer. Patients included in the validation cohort were treated with either doxorubicin or 5-FU and mitomycin NACT.ResultsDNA methylation patterns changed from before to after NACT in 5-year survivors, while no significant changes were observed in non-survivors or related to treatment response. DNA methylation changes included an overall loss of methylation at CpG islands and gain of methylation in non-CpG islands, and these changes affected genes linked to transcription factor activity, cell adhesion and immune functions. A risk score was developed based on four methylation sites which successfully predicted long-term survival in our cohort (p = 0.0034) and in an independent validation cohort (p = 0.049).ConclusionOur results demonstrate that DNA methylation patterns in breast tumors change in response to NACT. These changes in DNA methylation show potential as prognostic biomarkers for breast cancer survival.