Semi-parametric Cox Regression Research Articles

Clinical courses and predictors of left ventricular systolic dysfunction in systemic sclerosis: A cohort study.

Left ventricular systolic dysfunction (LVSD) is a cardiac involvement that is the leading cause of death among patients with systemic sclerosis (SSc). We aimed to define the clinical course and predictors of LVSD among SSc patients. We conducted a cohort study among adult patients with SSc who were followed up from 2013 to 2020. Semiparametric Cox regression analysis with robust clustering by cohort identification number was used to evaluate the predictors of LVSD. Among the 3, 987 person-years, LVSD was defined in 35 of 419 SSc patients for an incidence of 0.88 per 100 person-years. The median duration of the disease was 8.5 (interquartile range (IQR) 4.9-12.9) years. Every 1-point increase in the modified Rodnan skin score (mRSS) and salt and pepper skin were strong predictors of LVSD, with a respective adjusted hazard ratio (HR) of 1.05 and 3.17. During follow-up, 26 cases (74.3%) had unimproved LVSD. The strong predictors of the unimprovement of LVSD were every 1-point increase in mRSS (HR 1.05), every 1 mg increase in prednisolone treatment (HR 1.05), and every 1 U/L increase in creatine kinase (CK) (HR 1.001). Mycophenolate treatment was a protective factor against the unimprovement of LVSD in SSc (HR 0.15). LVSD was frequently found in patients with diffuse cutaneous SSc, and in most cases, it remained unimproved during follow-up. High mRSS, steroid use, and high CK levels were predictors of unimproved LVSD, whereas mycophenolate treatment might prevent the progression of LVSD. Steroids should be prescribed with caution in patients with longer disease duration.

Complications and associated risk factors after surgical management of proximal femoral fractures.

This work aimed at answering the following research questions: 1) What is the rate of mechanical complications, nonunion and infection for head/neck femoral fractures, intertrochanteric fractures, and subtrochanteric fractures in the elderly USA population? and 2) Which factors influence adverse outcomes? Proximal femoral fractures occurred between 1 January 2009 and 31 December 2019 were identified from the Medicare Physician Service Records Data Base. The Kaplan-Meier method with Fine and Gray sub-distribution adaptation was used to determine rates for nonunion, infection, and mechanical complications. Semiparametric Cox regression model was applied incorporating 23 measures as covariates to identify risk factors. Union failure occured in 0.89% (95% confidence interval (CI) 0.83 to 0.95) after head/neck fracturs, in 0.92% (95% CI 0.84 to 1.01) after intertrochanteric fracture and in 1.99% (95% CI 1.69 to 2.33) after subtrochanteric fractures within 24 months. A fracture-related infection was more likely to occur after subtrochanteric fractures than after head/neck fractures (1.64% vs 1.59%, hazard ratio (HR) 1.01 (95% CI 0.87 to 1.17); p < 0.001) as well as after intertrochanteric fractures (1.64% vs 1.13%, HR 1.31 (95% CI 1.12 to 1.52); p < 0.001). Anticoagulant use, cerebrovascular disease, a concomitant fracture, diabetes mellitus, hypertension, obesity, open fracture, and rheumatoid disease was identified as risk factors. Mechanical complications after 24 months were most common after head/neck fractures with 3.52% (95% CI 3.41 to 3.64; currently at risk: 48,282). The determination of complication rates for each fracture type can be useful for informed patient-clinician communication. Risk factors for complications could be identified for distinct proximal femur fractures in elderly patients, which are accessible for therapeutical treatment in the management.

What Are the Mortality, Infection, and Nonunion Rates After Periprosthetic Femoral Fractures in the United States?

What Are the Mortality, Infection, and Nonunion Rates After Periprosthetic Femoral Fractures in the United States?

P-752 Cervical cerclage versus vaginal progesterone in the prevention of preterm birth in singleton pregnancies among women with a short cervical length: A retrospective cohort study

Abstract Study question To compare the maternal and neonatal effects of cervical cerclage and vaginal progesterone in preventing singleton preterm births in women with a short cervical length. Summary answer Cervical cerclage showed no benefit in preventing preterm birth; however, it prolonged gestation by 39 days compared to vaginal progesterone treatment. What is known already Clinically, there may be a bias toward the choice of cervical cerclage if the cervix is short (&amp;lt;10 mm) and, similarly, toward vaginal progesterone use if the cervix is long (&amp;gt;30 mm). However, there are no clear treatment guidelines for the best options for singleton pregnant women with a CL between 10 and 30 mm. Furthermore, there is insufficient evidence to determine whether one treatment is superior to the other in preventing PTB and decreasing adverse neonatal outcomes in singleton pregnancies in such cases. Study design, size, duration Asymptomatic pregnant women having singleton pregnancies, with a CL between 10 and 30 mm, measured using transvaginal ultrasound at 12–26 weeks of gestation, who delivered at our hospital between January 2009 and August 2020, were included in our study. Based on the inclusion and exclusion criteria, 267 singleton pregnant women, of whom 116 were treated with cervical cerclage and 151 with vaginal progesterone, were finally included. Participants/materials, setting, methods Independent sample t-tests and differential analysis were used to analyze the data based on their distribution. The Cox semi-parametric regression model was used to analyze the gestation weeks at delivery and neonatal outcomes. The decision regarding cesarean delivery was based on a binary logistic regression model. Main results and the role of chance In the initial analysis, the number of preterm births was significantly higher in the cerclage group than in the vaginal progesterone group; however, after multivariate adjustment for confounding factors, the latency period from diagnosis to delivery was found to be significantly prolonged in the cerclage group. Limitations, reasons for caution There are currently no uniform criteria for determining whether study subjects are eligible for cervical cerclage or vaginal progesterone treatment, which may present some cases of noncompliance. Wider implications of the findings In our study, we found that cervical cerclage did not have significant advantages over vaginal progesterone treatment in preventing PTB. However, upon adjustment for confounding factors, it was shown to prolong the gestational age by 39 days compared to vaginal progesterone treatment. Trial registration number non-clinical trials

Survival of the fittest: do firms actively or passively learn survival?

PurposeIn the corporate world, there is no certainty of survival. This research aims to identify firm-level factors that increase or decrease a firm's probability of exit and survival.Design/methodology/approachThe study examines 153 listed textile sector firms in Pakistan over a 10-year period from 2009 to 2018, comprising 1,413 observations. The semi-parametric Cox regression model is used to process the results.FindingsThe study finds that larger and exporting firms are more likely to survive, while those with a high ratio of fixed assets to total assets, high expenditure on advertising and variable costs are less likely to survive. The relationship between age and firm survival is inconclusive.Research limitations/implicationsAdaptability to the external environment provides a competitive advantage that is crucial for textile firms to reduce their chances of exit. The research is valuable for strategic managers and policymakers to identify focus areas to prevent firm exit.Originality/valueThis study supports the active learning theory, which suggests that new entrants in the textile sector of Pakistan should focus on becoming active market players, increasing efficiency and reducing variable costs to survive.

Proximal Humerus Fractures in the Elderly U.S. Population: A Cross-Sectional Study of Treatment Trends and Comparison of Complication Rates after Joint Replacement, Open Reduction and Internal Fixation, and Non-Surgical Management.

Proximal humerus fracture (PHF) treatment remains challenging. Multiple therapy options exist, and the optimal choice of management has been increasingly discussed in the literature. The aim of this study was to (1) analyze trends in the propensity of proximal humerus fracture treatments and (2) compare complication rates after joint replacement, surgical repair, and non-surgical treatment in terms of mechanical complications, union failure, and infection rates. In this cross-sectional study, patients aged 65 years or older with proximal humerus fractures occurring between 1 January 2009 and 31 December 2019 were identified from Medicare physician service claims records. The Kaplan-Meier method with the Fine and Gray adjustment was used to calculate the cumulative incidence rates for malunion/nonunion, infection, and mechanical complications for the following treatment categories: shoulder arthroplasty, open reduction and internal fixation (ORIF), and non-surgical treatment, respectively. Semiparametric Cox regression was performed incorporating 23 demographic, clinical, and socioeconomic covariates to determine risk factors. Between 2009 through 2019, conservative procedures decreased by 0.9%. ORIF procedures decreased from 9.51% (95% CI: 8.7-10.4) to 6.95% (95% CI: 6.2-7.7), whereas shoulder arthroplasties rose from 1.99% (95% CI: 1.6-2.4), to 5.45% (95% CI: 4.8-6.2). PHFs managed through ORIF were associated with higher union failure rates compared to conservatively treated fractures (HR = 1.31, 95% CI: 1.15-1.5, p < 0.001). The risk of developing an infection was increased after joint replacement compared to ORIF (2.66% vs. 1.09%, HR = 2.09, 95% CI: 1.46-2.98, p < 0.001). Mechanical complications were more common after joint replacement (6.37% vs. 4.85%, HR = 1.66, 95% CI: 1.32-2.09, p < 0.001). Complication rates differed significantly across treatment modalities. This should be considered when choosing a management procedure. Vulnerable elderly patient cohorts could be identified, and the optimization of modifiable risk factors might lead to a decrease of complication rates in both surgically and non-surgically treated patients.

Femoral shaft fractures in eldery patients – An epidemiological risk analysis of incidence, mortality and complications

ObjectivesThis work aimed at answering the following research questions: (1) What is the incidence of femoral shaft fractures in the geriatric population in the U.S.? (2) What is the rate of mortality, mechanical complications, nonunion and infection, and what are the associated risk factors? Study design and settingIn this cross-sectional study, femoral shaft fractures occurred between January 1, 2009, and December 31, 2019, were identified from Medicare records. Rates of mortality, nonunion, infection, and mechanical complications were calculated with the Kaplan-Meier method with Fine and Gray sub-distribution adaptation. Semiparametric Cox regression was applied with twenty-three covariates to determine risk factors. ResultsBetween 2009 through 2019 the incidence of femoral shaft fractures decreased by 12.07% to 40.8/100,000 inhabitants (p = 0.549). The 5-year mortality risk was 58.5%. Male sex, age over 75 years, chronic obstructive pulmonary disease, cerebrovascular disease, chronic kidney disease, congestive heart failure, diabetes mellitus, osteoporosis, tobacco dependence, and lower median household income were significant risk factors. The infection rate was 2.22% [95%CI: 1.90–2.58] and the union failure rate 2.52% [95%CI: 2.17–2.92] after 24 months. ConclusionAn early assessment of individual patient risk factors may be beneficial in the care and treatment of patients with these fractures.

Predictors for the Longevity of People with Diabetes in Buno Bedele and Illubabor Zones, South-west Ethiopia.

Currently, diabetes is a global health problem and it affects many people, especially in the developing continents. As patients' living conditions improve and the science of medicine advances, the longevity of such patients has increased greatly. Therefore, the purpose of this study was to identify predictors for the association of the longevity of people with diabetes in Buno Bedele and Illubabor Zones, South-west Ethiopia. The study applied a retrospective cohort study design approach. In particular, long rank tests for longevity experience and Cox semi-parametric regression were implemented to compare and investigate the predictors associated with the longevity of patients with diabetes. Among all the patients who participated in this study, 56.9% were females and the rest were males. From the Cox regression result, age (AHR = 1.0550, 95% CI: (1.0250, 1.0860), p-value = 0.001), female patients (AHR = 0.2200, 95% CI: (0.0390, 0.5290)), rural patients (AHR = 0.2200, 95% CI: (0.1000, 0.4890), p-value = 0.001), the existence of fasting blood glucose complication (AHR = 1.2040, 95% CI: (1.0930, 1.4460), p-value = 0.001), the existence of blood pressure (AHR = 1.2480, 95% CI: (1.1390, 1.5999), p-value = 0.0180), treatment type, Sulfonylureas (AHR = 4.9970, 95% CI: (1.4140, 17.6550), p-value = 0.0120), treatment type, Sulfonylurea and Metformin (AHR = 5.7200, 95% CI: (1.7780, 18.3990), p-value = 0.0030) were significantly affected the longevity of people with diabetes. The findings of the current study showed that the patient's age, sex of patients, residence area, the existence of complications, existence of pressure, and treatment type were major risk factors related to the longevity of people with diabetes. Hence, health-related education should be given to patients who come to take treatment to have better longevity for people with diabetes. More attention should be given to aged patients, male and urban patients, patients under complication treatment, and patients under treatment with single-treatment medication.

Proximal humerus fractures – epidemiology, comparison of mortality rates after surgical versus non-surgical treatment, and analysis of risk factors based on Medicare registry data

The optimal choice of management for proximal humerus fractures (PHFs) has been increasingly discussed in the literature, and this work aimed to answer the following questions: 1) what are the incidence rates of PHF in the geriatric population in the USA; 2) what is the mortality rate after PHF in the elderly population, specifically for distinct treatment procedures; and 3) what factors influence the mortality rate? PHFs occurring between 1 January 2009 and 31 December 2019 were identified from the Medicare physician service records. Incidence rates were determined, mortality rates were calculated, and semiparametric Cox regression was applied, incorporating 23 demographic, clinical, and socioeconomic covariates, to compare the mortality risk between treatments. From 2009 to 2019, the incidence decreased by 11.85% from 300.4 cases/100,000 enrollees to 266.3 cases/100,000 enrollees, although this was not statistically significant (z = -1.47, p = 0.142). In comparison to matched Medicare patients without a PHF, but of the same five-year age group and sex, a mean survival difference of -17.3% was observed. The one-year mortality rate was higher after nonoperative treatment with 16.4% compared to surgical treatment with 9.3% (hazard ratio (HR) = 1.29, 95% confidence interval (CI) 1.23 to 1.36; p < 0.001) and to shoulder arthroplasty with 7.4% (HR = 1.45, 95% CI 1.33 to 1.58; p < 0.001). Statistically significant mortality risk factors after operative treatment included age older than 75 years, male sex, chronic obstructive pulmonary disease (COPD), cerebrovascular disease, chronic kidney disease, a concomitant fracture, congestive heart failure, and osteoporotic fracture. Mortality risk factors for distinct treatment modes after PHF in elderly patients could be identified, which may guide clinical decision-making.Cite this article: Bone Joint Res2023;12(2):103-112.

Revision Rates and Associated Risk Factors after Shoulder Arthroplasty.

This study aims at answering the following questions (1) How high is the revision rate after osteoarthritis-, and rotator cuff-related compared to proximal humerus fracture (PHF)-related shoulder arthroplasty? (2) What are the associated risk factors for a revision after shoulder arthroplasty? Shoulder arthroplasty procedures occurring between 1 January 2009 and 31 December 2019 were identified from the Medicare database. First, revision rates for PHF patients and age- and sex-matched non-fracture patients, grouped into osteoarthritis-related and rotator cuff-related arthroplasty, were compared. Second, revision rates between total shoulder arthroplasty and hemiarthroplasty after PHF were compared. Semiparametric Cox regression was applied, incorporating 23 demographic, clinical, and socioeconomic covariates, to investigate risk factors for revision surgery. Between the considered time period from 2009 through 2019, a total number of 47,979 PHFs was identified. A shoulder arthroplasty procedure was performed in n = 2639 (5.5%, 95%CI: 4.8-6.1) of the cases. The five-year survivorship of the implant was 96.3 (95%CI: 93.8-97.9) after hemiarthroplasty and 96.1% (05%CI: 94.2-97.3) after total shoulder arthroplasty. To compare the revision rates, n = 14,775 patients with osteoarthritis and n = 4268 patients with rotator cuff arthropathy, who received a shoulder arthroplasty, served as a non-fracture control group. Patients receiving a rotator cuff-related arthroplasty were more likely to require a revision compared to patients treated for osteoarthritis (HR: 1.27, 95%CI: 1.04-1.44, p = 0.018). Identified significant risk factors for revision surgery after shoulder arthroplasty included age ≤ 75 years, male sex, and osteoporosis. High implant survival was found for hemiarthroplasty and total shoulder arthroplasty for the treatment of PHF in elderly patients. The risk of revision surgery was elevated in patients receiving a rotator cuff-related arthroplasty as well as in patients with osteoporosis, male patients and patients older than 75 years.

Survival Benefit of Birtamimab in Mayo Stage IV AL Amyloidosis in the Phase 3 VITAL Study Consistent after Adjustment for Key Baseline Variables

Introduction: Amyloid light chain (AL) amyloidosis - a progressive disorder caused by misfolded light chains produced by plasma cells - is associated with high mortality, poor quality of life, and increased healthcare costs, particularly in newly diagnosed patients with advanced disease (Mayo 2012 Stage IV, median overall survival <6 months). Birtamimab is a monoclonal antibody designed to neutralize circulating soluble and deplete deposited insoluble amyloid by promoting phagocytic clearance. In 2018, the Phase 3 VITAL study - a multicenter, global, randomized, double-blind, placebo-controlled study (NCT02312206) conducted in newly diagnosed, treatment-naive patients with AL amyloidosis and cardiac involvement - was terminated based on a futility analysis of the primary endpoint (time to all-cause mortality [ACM] or time to cardiac hospitalization ≥91 days after first study drug infusion); the final hazard ratio (HR) numerically favored birtamimab + standard of care (SOC) over placebo + SOC (0.826 [95% CI: 0.574, 1.189]). Post hoc analysis of ACM over 9 months revealed a significant survival benefit (HR=0.413 [95% CI: 0.191, 0.895]) in patients at high risk for early death (i.e., Mayo 2012 Stage IV). Here we report the results of sensitivity analyses of ACM in the subgroup of patients with Mayo 2012 Stage IV AL amyloidosis, adjusting for key baseline variables. Methods: For ACM, the hazard ratio and 90% two-sided confidence interval were estimated from the semi-parametric Cox Regression model stratified by randomization strata (i.e., Mayo Stage I/II vs III/IV, renal stage I vs II/III, and 6MWT [6-minute walk test] distance). Separately, baseline variables including age, sex, race, ethnicity, age at diagnosis, duration since diagnosis, NT-proBNP (N-terminal pro-brain natriuretic peptide), dFLC (difference between involved and uninvolved free light chain), FLC (free light chain), NYHA (New York Heart Association) class, troponin-T, and 6MWT distance were added to the Cox Regression model to evaluate the impact on the overall survival benefit. All adjudicated deaths prior to 9 months were included in the analysis. Patients who had no events were censored at 9 months. Results: Of the 260 patients enrolled in the VITAL study, 77 (29.6%) were characterized as Mayo 2012 Stage IV at baseline, 38 randomized to birtamimab + SOC and 39 to placebo + SOC. These patients had a median age of 64 years and were primarily white (93.5%) and male (68.8%). Baseline demographic and clinical characteristics were generally balanced between the two treatment groups among these Mayo Stage IV patients. After adjustment for key baseline demographic, clinical, and laboratory variables, the adjusted hazard ratios with each of the baseline variables added separately to the Cox Regression model range from 0.336 to 0.465, with all the upper bounds of the 90% confidence interval less than 1 (Figure). Conclusions: Birtamimab is the only investigational therapeutic that has shown a significant survival benefit in Mayo Stage IV AL amyloidosis patients. The survival benefit of birtamimab was consistent across all key baseline variables, including demographic factors (age, sex, race, ethnicity), clinical characteristics (age at diagnosis, duration since diagnosis, NYHA class, 6MWT distance), and laboratory parameters (NT-proBNP, dFLC, FLC, troponin-T), reinforcing the strength of the survival data in Mayo Stage IV patients. The AFFIRM-AL study, designed to confirm the VITAL study results in Mayo Stage IV AL amyloidosis patients, is currently active and enrolling. Figure 1View largeDownload PPTFigure 1View largeDownload PPT Close modal

Interpretability of SurvivalBoost upon Shapley Additive Explanation value on medical data

Machine learning methods have been extensively used in survival analysis. SurvivalBoost - a machine-learning-based survival regression algorithm, focused on Elastic-net-Type penalized semiparametric Cox regression model on XGBoost and random survival forests, has been verified its superior prediction performance on real and simulated datasets. Whereas the interpretability is remain undiscovered. This paper discusses the interpretability of this algorithm upon using the Shapley Additive Explanation (SHAP) value. It is illustrated that the algorithm can be more effective to guide the diagnosis and practice of survival analysis.

Determinants of Stroke Mortality through Survival Models: The Case of Mettu Karl Referral Hospital, Mettu, Ethiopia.

Introduction Every year worldwide, between five to six million deaths are associated with stroke; on average, one stroke-related death occurs every four minutes. In Ethiopia, stroke is a frequent cause of mortality and morbidity from noncommunicable diseases. Therefore, this study was aimed at determining factors associated to stroke mortality through survival models in Mettu Karl Referral Hospital. Methods This study was conducted from September 1, 2014, to April 1, 2017, and encompassed 202 stroke patients at Mettu Karl Referral Hospital. The Cox semiparametric regression was used for analyzing survival analysis of stroke patients using R software. Results A total of 202 stroke patients were included in the study, and among those patients, 72.8% and 27.2% were censored and died, respectively. According to the result of Cox semiparametric regression model, sex of patients, hypertension, baseline complication, and stroke type had significant effect on survival of the stroke patient at 5% significance level. Conclusion The results from Cox semiparametric regression model indicated that sex of patients, hypertension, baseline complication, and stroke type were major factors related to the survival time of stroke patients. The researcher recommends that the people should be aware on the burden of those risk factors and well informed about the disease.

Penalized semiparametric Cox regression model on XGBoost and random survival forests

The objective of this paper is to propose an efficient regression algorithm of survival analysis - SurvivalBoost.. This algorithm is based on Random Survival Forests (RSF) and XGBoost. By combining the Elastic-Net penalty type Cox proportional hazards regression model with XGBoost optimal algorithm, our algorithm is more suitable for survival analysis. The performance of the proposed algorithm is compared with the Cox proportional hazards regression model, XGBoost, CoxBoost, RSF and Gradient Boosting Desicion Tree-based survival regression model on 4 simulated datasets and 4 real survival datasets. The results illustrated the superiority of the proposed algorithm.

English

Family farms are poorly modernized in Burkina Faso despite their predominance in the country&rsquo;s agriculture and their major contribution to national food production. Convincing evidence of the contribution of family farm modernization to food security is needed to support advocacy. This study used data from recent national longitudinal surveys and Cox semi-parametric regression methods to explore the effect of factors of modernization on the food security of farm households in Burkina Faso. The results showed that the training of agricultural workers, ownership of traction animals, and use of improved seeds reduced the risk of food-secure households falling into food insecurity by 22.8, 21.6, and 14.9%, respectively. These three factors significantly determine the stability of households&rsquo; food security, suggesting that the modernization of family farms could contribute to the prevention of food insecurity in Burkina Faso. A key strength of this study is that it was able to capitalize on the wealth of these data, which come from national surveys that are representative of farm households at the provincial level, longitudinal and prospective, making it possible to track the same households over time, at an annual frequency. Key words: Agricultural modernization, family farming, food security, Burkina Faso

Comparison of Cox Regression and Parametric Models for Survival Analysis of Genetic Variants in Hnf1b Gene Related to Age at Onset of Cancer

Semi-parametric Cox regression and parametric methods have been used to analyze survival data of cancer; however, no study has focused on the comparison of survival models in genetic association analysis of age at onset (AAO) of cancer. The Hepatocyte nuclear factor-1- beta (HNF1B) gene has been associated with risk of endometrial and prostate cancers; however, no study has focused on the effect of HNF1B gene on the AAO of cancer. This study examined 23 single nucleotide polymorphisms (SNPs) within the HNF1B gene in the Marshfield sample with 716 cancer cases and 2,848 non-cancer controls. Cox proportional hazards models in PROC PHREG and parametric survival models (including exponential, Weibull, log-normal, log-logistic, and gamma models) in PROC LIFEREG in SAS 9.4 were used to detect the genetic association of HNF1B gene with the AAO. The Akaike information criterion (AIC) and Bayesian information criterion (BIC) were used to compare the Cox models and parametric survival models. Both AIC and BIC values showed that the Weibull distribution is the best model for all the 23 SNPs and the Gamma distribution is the second best. The top two SNPs are rs4239217 and rs7501939 with time ratio (TR) =1.08 (p&lt;0.0001 for the AA and AG genotypes, respectively) and 1.07 (p=0.0004 and 0.0002 for CC and CT genotypes, respectively) based on the Weibull model, respectively. This study shows that the parametric Weibull distribution is the best model for the genetic association of AAO of cancer and provides the first evidence of several genetic variants within the HNF1B gene associated with AAO of cancer.

Radiation-induced Hypothyroidism in Survivors of Head-and-Neck and Breast Cancers After 3-Dimensional Radiation Therapy: Dose-Response Models and Clinical-Dosimetric Predictors

Background: The prediction of normal tissue complications in treatment planning plays a critical role in radiation therapy of cancer. Objectives: The aim of the current study was to evaluate mathematical models and clinical-dosimetric variables for prediction of radiation-induced hypothyroidism (RHT) in patients with head-and-neck cancer (HNC) and breast cancer (BC). Methods: Clinical and dose-volume data from 62 patients treated with three-dimensional conformal radiation therapy were prospectively analyzed in terms of HNCs and BC. Thyroid function assessment was monitored by the level of thyroid hormones from patients’ serum samples. Cox semi-parametric regression models were used to predict the risk of RHT. Model performance and model ranking were evaluated in accordance with the area under the receiver operating characteristic curve (AUC) and Akaike’s information criterion (AIC), respectively. Results: Out of 62 patients, 17 persons developed RHT at a median follow-up of 11.4 months after radiation therapy. Thyroid volumes above the cut-off points of 14.2 cc and 11.4 cc showed a decrease in RHT risk for patients with HNC and BC, respectively. Moreover, the thyroid mean dose above the cut-off points of 53 and 27 Gy increased the risk of RHT for patients with HNC and BC, respectively. Simple and Multiple Cox regression analyses of the complete dataset revealed that thyroid volume and thyroid mean dose were the strongest predictors of RHT. According to AUC, Boomsma’s model, and the generalized equivalent-uniform-dose (EUD) model in the HNC dataset outperformed the BC dataset. Conclusions: The probability of RHT rises with an increase in the mean dose to the thyroid gland; however, it decreases with increasing thyroid gland volume. Regarding the AUC analysis, gEUD model showed an acceptable predictive performance; however, the logistic Boomsma’s model was somehow more effective in predicting RHT on the HNC dataset. Cella’s model revealed a relatively acceptable prediction of RHT on the BC dataset.

Importance of previous hospital stays on the risk of hospital re-admission in older adults: a real-life analysis of the PAERPA study population

consideration of the first hospital re-admission only and failure to take account of previous hospital stays, which are the two significant limitations when studying risk factors for hospital re-admission. The objective of the study was to use appropriate statistical models to analyse the impact of previous hospital stays on the risk of hospital re-admission among older patients. an exhaustive analysis of hospital discharge and health insurance data for a cohort of patients participating in the PAERPA ('Care Pathways for Elderly People at Risk of Loss of Personal Independence') project in the Hauts de France region of France. All patients aged 75 or over were included. All data on hospital re-admissions via the emergency department were extracted. The risk of unplanned hospital re-admission was estimated by applying a semiparametric frailty model, the risk of death by applying a time-dependent semiparametric Cox regression model. a total of 24,500 patients (median [interquartile range] age: 81 [77-85]) were included between 1 January 2015 and 31 December 2017. In a multivariate analysis, the relative risk (95% confidence interval [CI]) of hospital re-admission rose progressively from 1.8 (1.7-1.9) after one previous hospital stay to 3.0 (2.6-3.5) after five previous hospital stays. The relative risk [95%CI] of death rose slowly from 1.1 (1.07-1.11) after one previous hospital stay to 1.3 (1.1-1.5) after five previous hospital stays. analyses of the risk of hospital re-admission in older adults must take account of the number of previous hospital stays. The risk of death should also be analysed.

Psychiatric Adverse Events Associated With Infliximab: A Cohort Study From the French Nationwide Discharge Abstract Database.

IntroductionInfliximab (IFX) was the first anti-tumor necrosis factor (TNFα) antibody to be used in the treatment of severe chronic inflammatory diseases, such as Crohn’s disease and rheumatoid arthritis. A number of serious adverse drug reactions are known to be associated with IFX use; they include infections, malignancies, and injection site reactions. Although a few case reports have described potential psychiatric adverse events (including suicide attempts and manic episodes), the latter are barely mentioned in IFX’s summary of product characteristics. The objective of the present retrospective study was to detect potential psychiatric adverse events associated with IFX treatment by analyzing a national discharge abstract database.Materials and MethodsWe performed an historical cohort study by analyzing data from the French national hospital discharge abstract database (PMSI) between 2008 and 2014. All patients admitted with one of the five diseases treated with IFX were included.ResultsOf the 325,319 patients included in the study, 7,600 had been treated with IFX. The proportion of hospital admissions for one or more psychiatric events was higher among IFX-exposed patients (750 out of 7,600; 9.87%) than among non-exposed patients (17,456 out of 317,719; 5.49%). After taking account of potential confounders in the cohort as a whole, a semi-parametric Cox regression analysis gave an overall hazard ratio (HR) [95% confidence interval] (CI) of 4.5 [3.95; 5.13] for a hospital admission with a psychiatric adverse event during treatment with IFX. The HR (95%CI) for a depressive disorder was 4.97 (7.35; 6.68). Even higher risks were observed for certain pairs of adverse events and underlying pathologies: psychotic disorders in patients treated for ulcerative colitis (HR = 5.43 [2.01; 14.6]), manic episodes in patients treated for severe psoriasis (HR = 12.6 [4.65; 34.2]), and suicide attempts in patients treated for rheumatoid arthritis (HR = 4.45 [1.11; 17.9]).DiscussionThe present retrospective, observational study confirmed that IFX treatment is associated with an elevated risk of psychiatric adverse events. Depending on the disease treated, physicians should be aware of these potential adverse events.

Does race impact functional outcomes in patients undergoing robotic partial nephrectomy?

BackgroundThe role of race on functional outcomes after robotic partial nephrectomy (RPN) is still a matter of debate. We aimed to evaluate the clinical and pathologic characteristics of African American (AA) and Caucasian patients who underwent RPN and analyzed the association between race and functional outcomes.MethodsData was obtained from a multi-institutional database of patients who underwent RPN in 6 institutions in the USA. We identified 999 patients with complete clinical data. Sixty-three patients (6.3%) were AA, and each patient was matched (1:3) to Caucasian patients by age at surgery, gender, Charlson Comorbidity Index (CCI) and renal score. Bivariate and multivariate logistic regression analyses were used to evaluate predictors of acute kidney injury (AKI). Kaplan-Meier method and multivariable semiparametric Cox regression analyses were performed to assess prevalence and predictors of significant eGFR reduction during follow-up.ResultsOverall, 252 patients were included. AA were more likely to have hypertension (58.7% vs. 35.4%, P=0.001), even after 1:3 match. Overall 42 patients (16.7%) developed AKI after surgery and 35 patients (13.9%) developed significant eGFR reduction between 3 and 15 months after RAPN. On multivariate analysis, AA race did not emerge as a significant factor for predicting AKI (OR 1.10, P=0.8). On Cox multivariable analysis, only AKI was found to be associated with significant eGFR reduction between 3 and 15 months after RAPN (HR 2.49, P=0.019).ConclusionsAlthough African American patients were more likely to have hypertension, renal function outcomes of robotic partial nephrectomies were not significantly different when stratified by race. However, future studies with larger cohorts are necessary to validate these findings.