RESUMEN
Survival analysis following oncological treatments require specific analysis techniques to account for data considerations, such as failure to observe the time of event, patient withdrawal, loss to follow-up, and differential follow up. These techniques can include Kaplan-Meier and Cox proportional hazard analyses. However, studies do not always report overall survival (OS), disease-free survival (DFS), or cancer recurrence using hazard ratios, making the synthesis of such oncologic outcomes difficult. We propose a hierarchical utilization of methods to extract or estimate the hazard ratio to standardize time-to-event outcomes so that study inclusion into meta-analyses can be maximized. We also provide proof-of concept results from a statistical analysis that compares OS, DFS, and cancer recurrence for robotic surgery to open and non-robotic minimally invasive surgery. In our example, use of the proposed methodology would allow for the increase in data inclusion from 108 hazard ratios reported to 240 hazard ratios reported or estimated, resulting in an increase of 122%. While there are publications summarizing the motivation for these analyses, and comprehensive papers describing strategies to obtain estimates from published time-dependent analyses, we are not aware of a manuscript that describes a prospective framework for an analysis of this scale focusing on the inclusion of a maximum number of publications reporting on long-term oncologic outcomes incorporating various presentations of statistical data.
Asunto(s)
Oncología Médica/normas , Procedimientos Quirúrgicos Mínimamente Invasivos/normas , Neoplasias/cirugía , Procedimientos Quirúrgicos Robotizados/normas , Supervivencia sin Enfermedad , Humanos , Estimación de Kaplan-Meier , Laparoscopía/efectos adversos , Laparoscopía/normas , Neoplasias/epidemiología , Modelos de Riesgos Proporcionales , Análisis de Supervivencia , Resultado del TratamientoRESUMEN
Improving the efficiency of health care is a national priority. The purpose of this study was to estimate trends in the efficiency of nursing care. Specifically, the baseline and rate of change in efficiency in the association between select hospital and nursing unit characteristics (e.g., nurse staffing levels) and indicators of patient safety (e.g., fall rates and hospital-acquired pressure ulcer rates) was investigated. A small but significant improvement in efficiency for non-Magnet® hospitals and units with increased RN hours per patient day was found. Trends in efficiency varied by unit type, with medical units showing the greatest improvement. In general, efficiency improved most in health care settings having the greatest opportunity for improvement.