Analyzing Complex Cancer Studies With Skewed Responses

分析具有偏差反应的复杂癌症研究

• 批准号: 9288147
• 负责人: Stuart R. Lipsitz
• 金额: $ 8.33万
• 依托单位: BRIGHAM AND WOMEN'S HOSPITAL
• 依托单位国家: 美国
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-06-06 至 2018-11-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9288147
• 关键词: Accounting; Address; Analgesics; Bayesian Method; Biometry; Blood; Clinical; Clinical Investigator; Cluster Analysis; Collaborations; Complex; Data; Data Analyses; Documentation; Epidemiology; Equation; Future; Genitourinary system; Goals; Hospitals; Length; Literature; Malignant Neoplasms; Malignant neoplasm of urinary bladder; Methodology; Methods; Modeling; Observational Study; Oncologist; Operative Surgical Procedures; Outcome; Paper; Patients; Probability; Procedures; Publications; Publishing; Recurrence; Science; Seminal; Side; Statistical Data Interpretation; Statistical Methods; Statistical Models; Structure; Surgeon; Time; Time Study; Visit; attenuation; base; cancer clinical trial; clinically relevant; cost; follow-up; frailty; hazard; high dimensionality; interest; novel; public health relevance; response; semiparametric; sound; surgical pain; survival outcome; time interval; tool; treatment effect; treatment group; web site

 DESCRIPTION (provided by applicant): Many of the outcomes in seminal cancer studies are highly skewed. Moreover, the data are clustered within oncologist, practice, or hospital, and often the outcomes are right or interval censored, and there are a large number of predictors of interest. Because of the skewness in the outcomes, medians and quantiles of the outcome as a function of covariates is of interest. There is very limited current literature available to deal particularly with statistical models and analysis of clustered skewed response data. Here, to analyze such data, we propose methods in five aims that will have a high impact on clinical and biostatistical sciences and future cancer studies. In particular, the four aims are: 1).Quantile regression for highly skewed clustered outcomes (censored and not censored); 2) Methods for interval-censored data with a log-linear median; 3) Estimating covariate effects on quantiles of highly-skewed mixed response data (including zero-inflated type models); 4) Estimation and prediction for skewed responses when there are a large number of covariates. An additional goal is to make the newly developed statistical/epidemiological methodology widely accessible to nonstatisticians. For the methods described in each aim, we plan to create macros and procedures which can be used with existing, widely-used statistical packages (e.g., SAS and R). Statistical macros and procedures will be made available on our website, together with documentation on how to apply these macros to the examples analyzed in the resulting publications. The approaches we propose are specifically developed to answer important clinical questions that our clinical collaborators need to publish future clinical papers.

 描述（由适用提供）：第二次癌症研究中的许多结果高度偏斜。此外，数据聚集在肿瘤科医生，实践或医院中，通常的结果是正确的或间隔的公民，并且有大量关注的预测指标。由于结果的偏差，结果的中值和分位数是协变量的函数。当前的文献非常有限，特别是处理统计模型和聚类偏斜响应数据的分析。在这里，为了分析此类数据，我们提出了五个目标的方法，这些方法将对临床和生物统计学科学以及未来的癌症研究产生很大影响。特别是，这四个目标是：1）。高度偏斜的聚类结果（审查和未经审查）的量化回归； 2）使用对数线性中位数的间隔审查数据的方法； 3）估计对高压​​混合响应数据（包括零膨胀类型模型）的分位数的协变量影响； 4）当有大量协变量时，偏斜响应的估计和预测。另一个目标是使新开发的统计/流行病学方法论可为非统治者广泛使用。对于每个目标中描述的方法，我们计划创建可以与现有的，广泛使用的统计软件包（例如SAS和R）一起使用的宏和过程。统计宏和程序将在我们的网站上提供，以及有关如何将这些宏应用于结果出版物中分析的示例的文档。我们提出的方法是专门开发出来的，以回答我们临床合作者发表未来临床论文所需的重要临床问题。

项目成果

Categorical Data Analysis Using a Skewed Weibull Regression Model.

• DOI: 10.3390/e20030176
• 发表时间: 2018-03-07
• 期刊: Entropy (Basel, Switzerland)
• 作者: Caron R;Sinha D;Dey DK;Polpo A
• 通讯作者: Polpo A

Using Cox regression to develop linear rank tests with zero-inflated clustered data.

• DOI: 10.1111/rssc.12396
• 发表时间: 2020-04
• 期刊: Journal of the Royal Statistical Society. Series C, Applied statistics
• 作者: Lipsitz SR;Fitzmaurice GM;Sinha D;Cole AP;Meyer CP;Trinh QD
• 通讯作者: Trinh QD