PubTransformer

A site to transform Pubmed publications into these bibliographic reference formats: ADS, BibTeX, EndNote, ISI used by the Web of Knowledge, RIS, MEDLINE, Microsoft's Word 2007 XML.

Survival Analysis - Top 30 Publications

A Proposal for Progression-Free Survival Assessment in Patients with Early Progressive Cancer.

Progression-free survival (PFS), which is evaluated in oncology clinical trials, is determined based on tumor progression evaluated according to an assessment schedule. There is possibly a bias in median PFS and hazard ratio (HR) for PFS depending on the assessment schedule referring to randomized controlled trials (RCTs) in patients with metastatic colorectal cancer.

High RBM3 expression is associated with an improved survival and oxaliplatin response in patients with metastatic colorectal cancer.

High expression of the RNA-binding motif protein 3 (RBM3) has been shown to correlate, with prolonged survival in several malignant diseases and with the benefit of platinum-based chemotherapy in ovarian cancer. The aim of this study was to evaluate RBM3 in metastatic colorectal cancer (mCRC) as a prognostic factor for overall survival and in relation to benefit of first-line chemotherapy.

A Novel Derivation Predicting Survival After Primary Tumor Resection in Stage IV Colorectal Cancer: Validation of a Prognostic Scoring Model and an Online Calculator to Provide Individualized Survival Estimation.

A prognostic scoring model has been devised previously to predict survival following primary tumor resection in patients with metastatic colorectal cancer and unresectable metastases. This has yet to be validated.

Metastasis-Free Survival Is a Strong Surrogate of Overall Survival in Localized Prostate Cancer.

Purpose Adjuvant therapy for intermediate-risk and high-risk localized prostate cancer decreases the number of deaths from this disease. Surrogates for overall survival (OS) could expedite the evaluation of new adjuvant therapies. Methods By June 2013, 102 completed or ongoing randomized trials were identified and individual patient data were collected from 28 trials with 28,905 patients. Disease-free survival (DFS) and metastasis-free survival (MFS) were determined for 21,140 patients from 24 trials and 12,712 patients from 19 trials, respectively. We evaluated the surrogacy of DFS and MFS for OS by using a two-stage meta-analytic validation model by determining the correlation of an intermediate clinical end point with OS and the correlation of treatment effects on both the intermediate clinical end point and OS. Results Trials enrolled patients from 1987 to 2011. After a median follow-up of 10 years, 45% of 21,140 men and 45% of 12,712 men experienced a DFS and MFS event, respectively. For DFS and MFS, 61% and 90% of the patients, respectively, were from radiation trials, and 63% and 66%, respectively, had high-risk disease. At the patient level, Kendall's τ correlation with OS was 0.85 and 0.91 for DFS and MFS, respectively. At the trial level, R(2) was 0.86 (95% CI, 0.78 to 0.90) and 0.83 (95% CI, 0.71 to 0.88) from weighted linear regression of 8-year OS rates versus 5-year DFS and MFS rates, respectively. Treatment effects-measured by log hazard ratios-for the surrogates and OS were well correlated ( R(2), 0.73 [95% CI, 0.53 to 0.82] for DFS and 0.92 [95% CI, 0.81 to 0.95] for MFS). Conclusion MFS is a strong surrogate for OS for localized prostate cancer that is associated with a significant risk of death from prostate cancer.

Epistasis in genomic and survival data of cancer patients.

Cancer aggressiveness and its effect on patient survival depends on mutations in the tumor genome. Epistatic interactions between the mutated genes may guide the choice of anticancer therapy and set predictive factors of its success. Inhibitors targeting synthetic lethal partners of genes mutated in tumors are already utilized for efficient and specific treatment in the clinic. The space of possible epistatic interactions, however, is overwhelming, and computational methods are needed to limit the experimental effort of validating the interactions for therapy and characterizing their biomarkers. Here, we introduce SurvLRT, a statistical likelihood ratio test for identifying epistatic gene pairs and triplets from cancer patient genomic and survival data. Compared to established approaches, SurvLRT performed favorable in predicting known, experimentally verified synthetic lethal partners of PARP1 from TCGA data. Our approach is the first to test for epistasis between triplets of genes to identify biomarkers of synthetic lethality-based therapy. SurvLRT proved successful in identifying the known gene TP53BP1 as the biomarker of success of the therapy targeting PARP in BRCA1 deficient tumors. Search for other biomarkers for the same interaction revealed a region whose deletion was a more significant biomarker than deletion of TP53BP1. With the ability to detect not only pairwise but twelve different types of triple epistasis, applicability of SurvLRT goes beyond cancer therapy, to the level of characterization of shapes of fitness landscapes.

A score test for comparing cross-sectional survival data with a fraction of non-susceptible patients and its application in clinical immunology.

In cross-sectional studies of time-to-event data collected by patient examinations at a single random point in time, a fraction of them will not experience the event regardless of the length of the follow-up time. This is the case in clinical immunology studies that include a mixed population, with both immune-reactive and immune-tolerant (or non-susceptible) patients. In these cases, classical tests of current status data may perform poorly. New methods for testing these data are needed.

Appropriate Use of Effective Dose in Radiation Protection and Risk Assessment.

Effective dose was introduced by the ICRP for the single, over-arching purpose of setting limits for radiation protection. Effective dose is a derived quantity or mathematical construct and not a physical, measurable quantity. The formula for calculating effective dose to a reference model incorporates terms to account for all radiation types, organ and tissue radiosensitivities, population groups, and multiple biological endpoints. The properties and appropriate applications of effective dose are not well understood by many within and outside the health physics profession; no other quantity in radiation protection has been more confusing or misunderstood. According to ICRP Publication 103, effective dose is to be used for "prospective dose assessment for planning and optimization in radiological protection, and retrospective demonstration of compliance for regulatory purposes." In practice, effective dose has been applied incorrectly to predict cancer risk among exposed persons. The concept of effective dose applies generally to reference models only and not to individual subjects. While conceived to represent a measure of cancer risk or heritable detrimental effects, effective dose is not predictive of future cancer risk. The formula for calculating effective dose incorporates committee-selected weighting factors for radiation quality and organ sensitivity; however, the organ weighting factors are averaged across all ages and both genders and thus do not apply to any specific individual or radiosensitive subpopulations such as children and young women. Further, it is not appropriate to apply effective dose to individual medical patients because patient-specific parameters may vary substantially from the assumptions used in generalized models. Also, effective dose is not applicable to therapeutic uses of radiation, as its mathematical underpinnings pertain only to observed late (stochastic) effects of radiation exposure and do not account for short-term adverse tissue reactions. The weighting factors incorporate substantial uncertainties, and linearity of the dose-response function at low dose is uncertain and highly disputed. Since effective dose is not predictive of future cancer incidence, it follows that effective dose should never be used to estimate future cancer risk from specific sources of radiation exposure. Instead, individual assessments of potential detriment should only be based on organ or tissue radiation absorbed dose, together with best scientific understanding of the corresponding dose-response relationships.

Comorbidities in the diseasome are more apparent than real: What Bayesian filtering reveals about the comorbidities of depression.

Comorbidity patterns have become a major source of information to explore shared mechanisms of pathogenesis between disorders. In hypothesis-free exploration of comorbid conditions, disease-disease networks are usually identified by pairwise methods. However, interpretation of the results is hindered by several confounders. In particular a very large number of pairwise associations can arise indirectly through other comorbidity associations and they increase exponentially with the increasing breadth of the investigated diseases. To investigate and filter this effect, we computed and compared pairwise approaches with a systems-based method, which constructs a sparse Bayesian direct multimorbidity map (BDMM) by systematically eliminating disease-mediated comorbidity relations. Additionally, focusing on depression-related parts of the BDMM, we evaluated correspondence with results from logistic regression, text-mining and molecular-level measures for comorbidities such as genetic overlap and the interactome-based association score. We used a subset of the UK Biobank Resource, a cross-sectional dataset including 247 diseases and 117,392 participants who filled out a detailed questionnaire about mental health. The sparse comorbidity map confirmed that depressed patients frequently suffer from both psychiatric and somatic comorbid disorders. Notably, anxiety and obesity show strong and direct relationships with depression. The BDMM identified further directly co-morbid somatic disorders, e.g. irritable bowel syndrome, fibromyalgia, or migraine. Using the subnetwork of depression and metabolic disorders for functional analysis, the interactome-based system-level score showed the best agreement with the sparse disease network. This indicates that these epidemiologically strong disease-disease relations have improved correspondence with expected molecular-level mechanisms. The substantially fewer number of comorbidity relations in the BDMM compared to pairwise methods implies that biologically meaningful comorbid relations may be less frequent than earlier pairwise methods suggested. The computed interactive comprehensive multimorbidity views over the diseasome are available on the web at Co=MorNet: bioinformatics.mit.bme.hu/UKBNetworks.

Development and validation of a prognostic scoring model for Mycobacterium avium complex lung disease: an observational cohort study.

Patients with Mycobacterium avium complex (MAC) lung disease (LD) have a heterogeneous prognosis. This study aimed to develop and validate a prognostic scoring model for these patients using independent risk factors for survival.

Survival comparison between radical surgery and definitive chemoradiation in 267 esophageal squamous cell carcinomas in a single institution: A propensity-matched study.

To compare radical surgery with definitive chemoradiation (CRT) for esophageal squamous cell carcinoma using propensity score (PS) matching at our single institution.

Prognostic significance of marital status in breast cancer survival: A population-based study.

Research shows that married cancer patients have lower mortality than unmarried patients but few data exist for breast cancer. We assessed total mortality associated with marital status, with attention to differences by race/ethnicity, tumor subtype, and neighborhood socioeconomic status (nSES). We included, from the population-based California Cancer Registry, women ages 18 and older with invasive breast cancer diagnosed between 2005 and 2012 with follow-up through December 2013. We estimated mortality rate ratios (MRR) and 95% confidence intervals (CI) for total mortality by nSES, race/ethnicity, and tumor subtype. Among 145,564 breast cancer cases, 42.7% were unmarried at the time of diagnosis. In multivariable-adjusted models, the MRR (95% CI) for unmarried compared to married women was 1.28 (1.24-1.32) for total mortality. Significant interactions were observed by race/ethnicity (P<0.001), tumor subtype (P<0.001), and nSES (P = 0.009). Higher MRRs were observed for non-Hispanic whites and Asians/Pacific Islanders than for blacks or Hispanics, and for HR+/HER2+ tumors than other subtypes. Assessment of interactive effect between marital status and nSES showed that unmarried women living in low SES neighborhoods had a higher risk of dying compared with married women in high SES neighborhoods (MRR = 1.60; 95% CI: 1.53-1.67). Unmarried breast cancer patients have higher total mortality than married patients; the association varies by race/ethnicity, tumor subtype, and nSES. Unmarried status should be further evaluated as a breast cancer prognostic factor. Identification of underlying causes of the marital status associations is needed to design interventions that could improve survival for unmarried breast cancer patients.

Population effect model identifies gene expression predictors of survival outcomes in lung adenocarcinoma for both Caucasian and Asian patients.

We analyzed and integrated transcriptome data from two large studies of lung adenocarcinomas on distinct populations. Our goal was to investigate the variable gene expression alterations between paired tumor-normal tissues and prospectively identify those alterations that can reliably predict lung disease related outcomes across populations.

Advanced Stage at Presentation Remains a Major Factor Contributing to Breast Cancer Survival Disparity between Public and Private Hospitals in a Middle-Income Country.

Background: Survival disparities in cancer are known to occur between public and private hospitals. We compared breast cancer presentation, treatment and survival between a public academic hospital and a private hospital in a middle-income country. Methods: The demographics, clinical characteristics, treatment and overall survival (OS) of 2767 patients with invasive breast carcinoma diagnosed between 2001 and 2011 in the public hospital were compared with 1199 patients from the private hospital. Results: Compared to patients in the private hospital, patients from the public hospital were older at presentation, and had more advanced cancer stages. They were also more likely to receive mastectomy and chemotherapy but less radiotherapy. The five-year OS in public patients was significantly lower than in private patients (71.6% vs. 86.8%). This difference was largely attributed to discrepancies in stage at diagnosis and, although to a much smaller extent, to demographic differences and treatment disparities. Even following adjustment for these factors, patients in the public hospital remained at increased risk of mortality compared to their counterparts in the private hospital (Hazard Ratio: 1.59; 95% Confidence Interval: 1.36-1.85). Conclusion: Late stage at diagnosis appears to be a major contributing factor explaining the breast cancer survival disparity between public and private patients in this middle-income setting.

Influence of time interval from diagnosis to treatment on survival for oral cavity cancer: A nationwide cohort study.

We aimed to explore the relationship between the time interval from diagnosis to treatment and survival of oral cavity squamous cell carcinoma patients.

The prognostic efficacy and improvements of the 7th edition Union for International Cancer Control tumor-node-metastasis classifications for Chinese patients with gastric cancer: Results based on a retrospective three-decade population study.

This study aimed to evaluate survival trends for patients with gastric cancer in northeast China in the most recent three decades and analyze the applicability of the UICC tumor-node-metastasis (TNM) classification 7th edition for Chinese patients with gastric cancer. A review of all inpatient and outpatient records of patients with gastric cancer was conducted in the first hospital of China Medical University and the Liaoning Cancer Hospital and Institute. All patients who met the inclusion criteria and were seen from January 1980 through December 2009 were included in the study. The primary outcome was 5-year survival, which was analyzed according to decade of diagnosis and TNM classifications. From 1980 through 2009, the 5-year survival rates for patients with gastric cancer (n=2414) increased from 39.1% to 57.3%. Decade of diagnosis was significantly associated with patient survival (p = 0.013), and the 5-year survival rate in the 2000s was remarkably higher than that in the 1980s and 1990s (p = 0.004 and 0.049, respectively). When classified according to the UICC TNM classification of gastric cancer 7th edition, the prognoses of stage IIIA and stage IIIB patients were not significantly different (p = 0.077). However, if stage T4b and stage N0 patients were classified as stage IIIA, the prognoses of stage IIIA and stage IIIB patients were significantly different (p < 0.001). Hence, there was a significant difference in survival during the three time periods in Northeast China. Classifying stage T4b and stage N0 patients as stage IIIA according to the 7th edition of UICC gastric cancer TNM classifications better stratified Chinese patients and predicted prognoses.

CT Findings, Radiologic-Pathologic Correlation, and Imaging Predictors of Survival for Patients With Interstitial Pneumonia With Autoimmune Features.

The objective of this study is to determine the CT findings and patterns of interstitial pneumonia with autoimmune features (IPAF) and to assess whether imaging can predict survival for patients with IPAF.

The predictive value of baseline LDL-TG level on major adverse cardiovascular events in a followed up cohort population.

We aimed at identifying the predictive roles of Low-Density Lipoprotein Triglycerides (LDL-TG) for major adverse cardiovascular events (MACEs).

Progression-Free Survival as a Surrogate for Overall Survival in Clinical Trials of Targeted Therapy in Advanced Solid Tumors.

Over the past 15 years, targeted therapy has revolutionized the systemic treatment of cancer. In parallel, there has been a growing debate on the choice of end points in clinical trials in oncology. This debate basically hinges on the choice between overall survival (OS) and progression-free survival (PFS). PFS is advantageous because it is measured earlier than OS, requires a smaller sample size than OS to achieve the desired power, and is not influenced by cross-over. On the other hand, PFS is prone to measurement error and bias, and may not capture the entire treatment effect on the outcomes of most interest to patients with an incurable disease: a prolonged survival and improved quality of life. Therefore, how can we choose between two imperfect end points? The answer to this question would certainly be made easier if PFS could be demonstrated to be a valid surrogate for OS. The validation of a surrogate end point is best made using individual-patient data (IPD) from randomized trials, which allows for standardized assessments of the patient-level and the trial-level correlations between surrogate and final end points. Proper IPD meta-analytical evaluations for targeted agents have still been rare, and to our knowledge only three studies on this topic are currently available in the metastatic setting: one in breast cancer, one in colorectal cancer and one in lung cancer. Although these three studies suffer from limitations inherent to the availability of IPD and the design of the original clinical trials, they have not been able to validate PFS as surrogate for OS, because only modest correlations were found between these two end points, both at the patient and at the trial level. Even if properly conducted surrogate-endpoint evaluations have thus far been unsuccessful, these evaluations are a step in the right direction and can be expected to be applied on a much larger scale in the era of data sharing of clinical trials.

Solid Cancer Incidence among the Life Span Study of Atomic Bomb Survivors: 1958-2009.

This is the third analysis of solid cancer incidence among the Life Span Study (LSS) cohort of atomic bomb survivors in Hiroshima and Nagasaki, adding eleven years of follow-up data since the previously reported analysis. For this analysis, several changes and improvements were implemented, including updated dose estimates (DS02R1) and adjustment for smoking. Here, we focus on all solid cancers in aggregate. The eligible cohort included 105,444 subjects who were alive and had no known history of cancer at the start of follow-up. A total of 80,205 subjects had individual dose estimates and 25,239 were not in either city at the time of the bombings. The follow-up period was 1958-2009, providing 3,079,484 person-years of follow-up. Cases were identified by linkage with population-based Hiroshima and Nagasaki Cancer Registries. Poisson regression methods were used to elucidate the nature of the radiation-associated risks per Gy of weighted absorbed colon dose using both excess relative risk (ERR) and excess absolute risk (EAR) models adjusted for smoking. Risk estimates were reported for a person exposed at age 30 years with attained age of 70 years. In this study, 22,538 incident first primary solid cancer cases were identified, of which 992 were associated with radiation exposure. There were 5,918 cases (26%) that occurred in the 11 years (1999-2009) since the previously reported study. For females, the dose response was consistent with linearity with an estimated ERR of 0.64 per Gy (95% CI: 0.52 to 0.77). For males, significant upward curvature over the full dose range as well as restricted dose ranges was observed and therefore, a linear-quadratic model was used, which resulted in an ERR of 0.20 (95% CI: 0.12 to 0.28) at 1 Gy and an ERR of 0.010 (95% CI: -0.0003 to 0.021) at 0.1 Gy. The shape of the ERR dose response was significantly different among males and females (P = 0.02). While there was a significant decrease in the ERR with increasing attained age, this decrease was more rapid in males compared to females. The lowest dose range that showed a statistically significant dose response using the sex-averaged, linear ERR model was 0-100 mGy (P = 0.038). In conclusion, this analysis demonstrates that solid cancer risks remain elevated more than 60 years after exposure. Sex-averaged upward curvature was observed in the dose response independent of adjustment for smoking. Findings from the current analysis regarding the dose-response shape were not fully consistent with those previously reported, raising unresolved questions. At this time, uncertainties in the shape of the dose response preclude definitive conclusions to confidently guide radiation protection policies. Upcoming results from a series of analyses focusing on the radiation risks for specific organs or organ families, as well as continued follow-up are needed to fully understand the nature of radiation-related cancer risk and its public health significance. Data and analysis scripts are available for download at: http://www.rerf.or.jp .

CT of Patients With Hip Fracture: Muscle Size and Attenuation Help Predict Mortality.

Our objective was to determine the association between muscle cross-sectional area and attenuation, as measured on routine CT scans, and mortality in older patients with hip fracture.

Meaningful endpoints for therapies approved for hematologic malignancies.

Overall survival (OS) is considered the gold standard for determining treatment efficacy in oncology trials, but the relation between treatment and OS can be challenging to assess because of long study durations and the impact of subsequent therapies on outcome. Using OS can be particularly difficult for new therapies in hematologic malignancies (HMs).

A single-center analysis of chronic graft-versus-host disease-free, relapse-free survival after alternative donor stem cell transplantation in children with hematological malignancies.

We assessed the clinical outcomes of allogeneic hematopoietic stem cell transplantation (SCT) from alternative donors for pediatric patients with hematological malignancies, defining graft-versus-host disease (GVHD)-free, relapse-free survival (GRFS) as a composite endpoint. We also defined chronic GVHD-free, relapse-free survival (cGRFS) as survival without severe chronic GVHD, relapse, or death. The probabilities of 2-year disease-free survival from a human leukocyte antigen (HLA) matched unrelated donor (n = 57), related donor with HLA-1 antigen mismatch in the graft-versus-host direction (1Ag-GvH-MMRD, n = 28), and unrelated umbilical cord blood (n = 35) were 52.2, 38.5, and 40.4%, respectively (P = 0.14), and for 2-year GRFS were 26.2, 13.4, and 30.4%, respectively (P = 0.089), and for 2-year cGRFS were 36.2, 16.7, and 40.4%, respectively (P = 0.015). Of the three groups, the 1Ag-GvH-MMRD group showed a significantly higher cumulative incidence of severe cGVHD, and was identified as a significant risk factor for worse cGRFS. These results suggest that intensification of GVHD prophylaxis may be needed for SCT from 1Ag-GvH-MMRD. As with GRFS, cGRFS should be used as an endpoint of the clinical study to predict long-term morbidity and mortality for patients who need longer follow-up such as pediatric SCT recipients.

Kaplan-Meier curve.

Exploring the key genes and signaling transduction pathways related to the survival time of glioblastoma multiforme patients by a novel survival analysis model.

This study is to explore the key genes and signaling transduction pathways related to the survival time of glioblastoma multiforme (GBM) patients.

What Kaplan-Meier survival curves don't tell us about CNS disease.

Central nervous system consequences of viral infections are rare, but when they do occur, they are often serious and clinically challenging to manage. Our awareness of the perils of neuroinvasion by viruses is growing: the recently appreciated impact of Ebola and Zika virus infections on CNS integrity, decreases in vaccination coverage for potentially neurotropic viruses such as measles, and increased neurovirulence of some influenza strains collectively highlight the need for a better understanding of the viral-neural interaction. Defining these interactions and how they result in neuropathogenesis is paramount for the development of better clinical strategies, especially given the limited treatment options that are available due to the unique physiology of the brain that limits migration of blood-borne molecules into the CNS parenchyma. In this perspective, we discuss some unique aspects of neuronal viral infections and immune-mediated control that impact the pathogenic outcomes of these infections. Further, we draw attention to an often overlooked aspect of neuropathogenesis research: that lack of overt disease, which is often equated with survival post-infection, likely only scratches the surface of the myriad ways by which neurotropic infections can impair CNS function.

Predicting Structure-Function Relations and Survival following Surgical and Bronchoscopic Lung Volume Reduction Treatment of Emphysema.

Lung volume reduction surgery (LVRS) and bronchoscopic lung volume reduction (bLVR) are palliative treatments aimed at reducing hyperinflation in advanced emphysema. Previous work has evaluated functional improvements and survival advantage for these techniques, although their effects on the micromechanical environment in the lung have yet to be determined. Here, we introduce a computational model to simulate a force-based destruction of elastic networks representing emphysema progression, which we use to track the response to lung volume reduction via LVRS and bLVR. We find that (1) LVRS efficacy can be predicted based on pre-surgical network structure; (2) macroscopic functional improvements following bLVR are related to microscopic changes in mechanical force heterogeneity; and (3) both techniques improve aspects of survival and quality of life influenced by lung compliance, albeit while accelerating disease progression. Our model predictions yield unique insights into the microscopic origins underlying emphysema progression before and after lung volume reduction.

MiRKAT-S: a community-level test of association between the microbiota and survival times.

Community-level analysis of the human microbiota has culminated in the discovery of relationships between overall shifts in the microbiota and a wide range of diseases and conditions. However, existing work has primarily focused on analysis of relatively simple dichotomous or quantitative outcomes, for example, disease status or biomarker levels. Recently, there is also considerable interest in the relationship between the microbiota and censored survival outcomes, such as in clinical trials. How to conduct community-level analysis with censored survival outcomes is unclear, since standard dissimilarity-based tests cannot accommodate censored survival times and no alternative methods exist.

Identifying survival-associated modules from the dysregulated triplet network in glioblastoma multiforme.

Long noncoding RNAs (lncRNAs) can act as competitive endogenous RNAs (ceRNAs) to compete with mRNAs for binding miroRNAs (miRNAs). The dysregulated triplets, composed by mRNAs, lncRNAs, and miRNAs, contributed to the development and progression of diseases, such as cancer. However, the roles played by triplet biomarkers are not fully understand in glioblastoma multiforme (GBM) patient survival.

Double-stenting in distal left main lesions: Let's crush.

Unprotected distal left main (ULM) lesions often require double-stenting. In the MITO Registry, a mini-crush stenting technique was safer than culotte stenting. Performing mini-crush arises as the best approach in patients with distal ULM lesions requiring elective double-stenting.