Open AccessStatistical issues and methods in designing and analyzing survival studies
Author(s) -
Perera Muditha,
Dwivedi Alok Kumar
Publication year - 2020
Publication title -
cancer reports
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.261
H-Index - 5
ISSN - 2573-8348
DOI - 10.1002/cnr2.1176
Subject(s) - statistical inference , context (archaeology) , computer science , statistical model , event (particle physics) , research design , data science , statistical analysis , survival analysis , data mining , medicine , management science , statistics , machine learning , mathematics , engineering , paleontology , physics , quantum mechanics , biology
Background Cancer studies that are designed for early detection and screening, or used for identifying prognostic factors, or assessing treatment efficacy and health outcome are frequently assessed with survival or time‐to‐event outcomes. These studies typically require specific methods of data analysis. Appropriate statistical methods in the context of study design and objectives are required for obtaining reliable results and valid inference. Unfortunately, variable methods for the same study objectives and dubious reporting have been noticed in the survival analysis of oncology research. Applied researchers often face difficulties in selecting appropriate statistical methods due to the complex nature of cancer studies. Recent findings In this report, we describe briefly major statistical issues along with related challenges in planning, designing, and analyzing of survival studies. For applied researchers, we provided flow charts for selecting appropriate statistical methods. Various available statistical procedures in common statistical packages for applying survival analysis were classified according to different objectives of the study. In addition, an illustration of the statistical analysis of some common types of time‐to‐event outcomes was shown with STATA codes. Conclusions We anticipate that this review article assists oncology researchers in understanding important statistical concepts involved in survival analysis and appropriately select the statistical approaches for survival analysis studies. Overall, the review may help in improving designing, conducting, analyzing, and reporting of data in survival studies.