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Developing methods and software for fitting the Cox proportional hazards model to partly interval-censored data

Award Number: SC2GM135078
ORGANIZATION: NATIONAL INSTITUTE OF GENERAL MEDICAL SCIENCES
OPDIV: NIH
AWARD CLASS: DISCRETIONARY
AWARD ACTIVITY TYPE: SCIENTIFIC/HEALTH RESEARCH (INCLUDES SURVEYS)

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Title: Developing methods and software for fitting the Cox proportional hazards model to partly interval-censored data Abstract: Partly interval-censored time-to-event data arise frequently in medical studies for diseases that involve periodic examinations, such as cancer, HIV, infectious diseases, and diabetes. For example, progression-free survival (PFS), the most commonly used primary endpoint in phase III cancer clinical trials, is actually partly interval- censored as the time of death for a patient will be exactly known while the time of disease progression will be only known to fall between two imaging assessment timepoints. Due to the lack of well-developed methods and software, partly interval-censored data have been treated as right-censored data for analysis in clinical trials and medical studies, which introduces bias at the very beginning and may lead to invalid statistical inferences and erroneous medical conclusions. The proposed project contains four aims: (1) to develop a Bayesian semiparametric method for fitting the Cox proportional hazards model, the most commonly used survival regression model, to partly interval-censored data; (2) to develop a Bayesian semiparametric method for fitting the Cox proportional hazards model with spatial frailty to spatially correlated partly interval-censored data; (3) to develop a Bayesian semiparametric method for fitting a multiple-frailty proportional hazards model with frailty selection to clustered partly interval-censored data; (4) then based on the validated new methods, to construct an R package that is efficient, reliable, and user-friendly for medical investigators to use. R is the most used statistical computing and graphics software and is free to the public. Hence, such a tool will facilitate the search for effective new drugs and identification of risk factors, thereby lead to improvement in patient treatment and disease prevention for many diseases that are significantly affecting public health.


Issue Date FY	Funding FY	Legal Entity Name	Legal Entity Address	Legal Entity City	Legal Entity State	Legal Entity Zip Code	Legal Entity COUNTY	Legal Entity COUNTRY	Assistance Listing	Award Code	Budget Year	Action Date	Action Type	Action Amount

Issue Date FY: 2024 ( Subtotal = $0 )
2024	2022	RESEARCH FOUNDATION OF THE CITY UNIVERSITY OF NEW YORK	695 PARK AVE	NEW YORK	NY	10065	NEW YORK	USA	Biomedical Research and Research Training	000	3	10/16/2023	NON-COMPETING CONTINUATION	$0
														Subtotal = $0

Issue Date FY: 2022 ( Subtotal = $156,000 )
2022	2022	RESEARCH FOUNDATION OF THE CITY UNIVERSITY OF NEW YORK	695 PARK AVE	NEW YORK	NY	10065	NEW YORK	USA	Biomedical Research and Research Training	000	3	12/14/2021	NON-COMPETING CONTINUATION	$140,400
2022	2022	RESEARCH FOUNDATION OF THE CITY UNIVERSITY OF NEW YORK	695 PARK AVE	NEW YORK	NY	10065	NEW YORK	USA	Biomedical Research and Research Training	001	3	6/15/2022	NON-COMPETING CONTINUATION	$15,600
														Subtotal = $156,000

Issue Date FY: 2021 ( Subtotal = $156,000 )
2021	2021	RESEARCH FOUNDATION OF THE CITY UNIVERSITY OF NEW YORK	695 PARK AVE	NEW YORK	NY	10065	NEW YORK	USA	Biomedical Research and Research Training	001	2	2/17/2021	NON-COMPETING CONTINUATION	$15,600
2021	2021	RESEARCH FOUNDATION OF THE CITY UNIVERSITY OF NEW YORK	695 PARK AVE	NEW YORK	NY	10065	NEW YORK	USA	Biomedical Research and Research Training	000	2	12/22/2020	NON-COMPETING CONTINUATION	$140,400
														Subtotal = $156,000

Issue Date FY: 2020 ( Subtotal = $156,000 )
2020	2020	RESEARCH FOUNDATION OF THE CITY UNIVERSITY OF NEW YORK	695 PARK AVE	NEW YORK	NY	10065	NEW YORK	USA	Biomedical Research and Research Training	000	1	2/19/2020	NEW	$156,000
														Subtotal = $156,000

Grand Total All Awards = $468,000

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Developing methods and software for fitting the Cox proportional hazards model to partly interval-censored data

Award Number: SC2GM135078

ORGANIZATION: NATIONAL INSTITUTE OF GENERAL MEDICAL SCIENCES

OPDIV: NIH

AWARD CLASS: DISCRETIONARY

AWARD ACTIVITY TYPE: SCIENTIFIC/HEALTH RESEARCH (INCLUDES SURVEYS)

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