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Restricted mean survival time (RMST) is a clinically interpretable and meaningful survival metric that has gained popularity in recent years. Several methods are available for regression modeling of RMST, most based on pseudo-observations or what is essentially an inverse-weighted complete-case analysis. No existing RMST regression method allows for the covariate effects to be expressed as functions over time. This is a considerable limitation, in light of the many hazard regression methods that do accommodate such effects. To address this void in the literature, we propose RMST methods that permit estimating time-varying effects. In particular, we propose an inference framework for directly modeling RMST as a continuous function of L. Large-sample properties are derived. Simulation studies are performed to evaluate the performance of the methods in finite sample sizes. The proposed framework is applied to kidney transplant data obtained from the Scientific Registry of Transplant Recipients.
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Tasa de Supervivencia , Modelos de Riesgos Proporcionales , Análisis de Regresión , Tamaño de la Muestra , Análisis de SupervivenciaRESUMEN
The impact of increasing body mass index (BMI) on development and progression of chronic kidney disease is established. Even implantation kidney biopsies from obese living donors demonstrate subtle histologic changes despite normal function. We hypothesized that kidneys from obese living (LD) and deceased donors (DD) would have inferior long-term allograft outcomes. In a study utilizing US transplant registry, we studied adult kidney transplant recipients from 2000 to 2014. Donors were categorized as BMI <20 (underweight), 20-25 (normal), 25-30 (overweight), 30-35 (mildly obese), and >35 kg/m2 (very obese). Our outcome of interest was death censored graft failure (DCGF). Cox proportional hazards model were fitted separately for recipients of DD and LD kidneys, and adjusted for donor, recipient, and transplant characteristics, including donor and recipient size mismatch ratio. Among 118 734 DD and 84 377 LD transplants recipients, we observed a significant and graded increase in DCGF risk among the overweight (LD:HR = 1.06, DD:HR = 1.04), mildly obese (LD:HR = 1.16, DD:HR = 1.10), and very obese (LD:HR = 1.22, DD:HR = 1.22) compared to normal BMI (P < 0.05). The graded effect of donor BMI on outcomes begins early and persists throughout the post-transplant period. Donor obesity status is an independent risk factor for inferior long-term renal allograft outcome despite adjusting for donor and recipient size mismatch and other donor, recipient, and transplant factors.
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Índice de Masa Corporal , Supervivencia de Injerto , Trasplante de Riñón , Donadores Vivos , Adulto , Humanos , Obesidad , Sistema de Registros , Estudios Retrospectivos , Factores de Riesgo , Resultado del TratamientoRESUMEN
Restricted mean survival time (RMST) has gained increased attention in biostatistical and clinical studies. Directly modeling RMST (as opposed to modeling then transforming the hazard function) is appealing computationally and in terms of interpreting covariate effects. We propose computationally convenient methods for evaluating center effects based on RMST. A multiplicative model for the RMST is assumed. Estimation proceeds through an algorithm analogous to stratification, which permits the evaluation of thousands of centers. We derive the asymptotic properties of the proposed estimators and evaluate finite sample performance through simulation. We demonstrate that considerable decreases in computational burden are achievable through the proposed methods, in terms of both storage requirements and run time. The methods are applied to evaluate more than 5000 US dialysis facilities using data from a national end-stage renal disease registry.
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Análisis de Supervivencia , Algoritmos , Bioestadística , Humanos , Fallo Renal Crónico/terapia , Modelos Estadísticos , Modelos de Riesgos Proporcionales , Sistema de Registros , Diálisis RenalRESUMEN
This article was migrated. The article was marked as recommended. Background:Chinese Americans are one of the fastest growing populations in the United States. However, 41% of Chinese Americans are not English proficient. Methods:In 2014, Medicine in Mandarin was established by the University of Michigan Medical School (UMMS) as a pre-clinical elective taught by a nationally certified healthcare Mandarin interpreter. A 32-hour curriculum was developed, including both didactics and interactive elements. Assessments included quizzes, standardized patient interviews, and a final exam. An evaluation was administered upon course completion, and a post-course survey was administered to graduates at least six months after course completion. Results:Between 2014 and 2017, the elective graduated 25 students, of whom 23 completed the course evaluation and 22 completed the post-course survey. Prior to the course, 9% of students felt comfortable practicing medicine in Mandarin. This increased to 78% of students post-course. When asked about subsequent clinical experiences, 82% of students reported having applied medical Mandarin skills. Overall, 96% rated the course as very good or excellent. Conclusion:A Medicine in Mandarin elective was well-received by students and improved their comfort in providing medical care in Mandarin. Additional study is warranted to examine the potential clinical impact of this course.
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BACKGROUND: The Kidney Donor Risk Index (KDRI) is a score applicable to deceased kidney donors which reflects relative graft failure risk associated with deceased donor characteristics. The KDRI is widely used in kidney transplant outcomes research. Moreover, an abbreviated version of KDRI is the basis, for allocation purposes, of the "top 20%" designation for deceased donor kidneys. Data upon which the KDRI model was based used kidney transplants performed between 1995 and 2005. Our purpose in this report was to evaluate the need to update the coefficients in the KDRI formula, with the objective of either (a) proposing new coefficients or (b) endorsing continued used of the existing formula. METHODS: Using data obtained from the Scientific Registry of Transplant Recipients, we analyzed n = 156069 deceased donor adult kidney transplants occurring from 2000 to 2016. Cox regression was used to model the risk of graft failure. We then tested for differences between the original and updated regression coefficients and compared the performance of the original and updated KDRI formulas with respect to discrimination and predictive accuracy. RESULTS: In testing for equality between the original and updated KDRIs, few coefficients were significantly different. Moreover, the original and updated KDRI yielded very similar risk discrimination and predictive accuracy. CONCLUSIONS: Overall, our results indicate that the original KDRI is robust and is not meaningfully improved by an update derived through modeling analogous to that originally employed.
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Rechazo de Injerto/epidemiología , Trasplante de Riñón/estadística & datos numéricos , Sistema de Registros , Medición de Riesgo/métodos , Donantes de Tejidos/estadística & datos numéricos , Receptores de Trasplantes/estadística & datos numéricos , Listas de Espera , Adulto , Supervivencia de Injerto , Humanos , Incidencia , Persona de Mediana Edad , Estudios Retrospectivos , Estados Unidos/epidemiologíaRESUMEN
Somatic reprogramming induced by defined transcription factors is a low-efficiency process that is enhanced by p53 deficiency. So far, p21 is the only p53 target shown to contribute to p53 repression of iPSC (induced pluripotent stem cell) generation, indicating that additional p53 targets may regulate this process. Here, we demonstrate that miR-34 microRNAs (miRNAs), particularly miR-34a, exhibit p53-dependent induction during reprogramming. Mir34a deficiency in mice significantly increased reprogramming efficiency and kinetics, with miR-34a and p21 cooperatively regulating somatic reprogramming downstream of p53. Unlike p53 deficiency, which enhances reprogramming at the expense of iPSC pluripotency, genetic ablation of Mir34a promoted iPSC generation without compromising self-renewal or differentiation. Suppression of reprogramming by miR-34a was due, at least in part, to repression of pluripotency genes, including Nanog, Sox2 and Mycn (also known as N-Myc). This post-transcriptional gene repression by miR-34a also regulated iPSC differentiation kinetics. miR-34b and c similarly repressed reprogramming; and all three miR-34 miRNAs acted cooperatively in this process. Taken together, our findings identified miR-34 miRNAs as p53 targets that play an essential role in restraining somatic reprogramming.