# Statistical methods for characterizing patients who highly-benefit from treatments and programs in Alzheimers, HIV, and other heterogeneous diseases

> **NIH NIH R01** · JOHNS HOPKINS UNIVERSITY · 2021 · $444,542

## Abstract

Project Summary
Accurate characterization of which patients benefit highly from a treatment or program in Alzheimer's or HIV dis-
eases are central for knowing which treatments work for which patients, and to plan effectively for the others. A
major challenge for this is heterogeneity of these diseases. Until now, treatment studies for Alzheimer's disease
with comorbidities have shown little if any efficacy. Also, for HIV/AIDS patients in resource -constrained settings,
only a small fraction use antiretroviral treatment (ART) or benefit from a given program to increase ART uptake.
Standard methods to characterize which patients benefit from such treatments/programs, first construct a predic-
tor using standard statistical criteria, and then use that predictor to characterize high-benefit patients. For such
methods, therefore, the clinical goal – to characterize high-benefit patients – is considered only at the implemen-
tation stage, and is not used for the construction of the method. In earlier work, we have shown that such methods
can dramatically misrepresent high-benefit patients; and we have developed a type of method that directly links
the clinical goal (high benefit) into the construction of the characterization mechanism. We were motivated by: a
study to reduce agitation in patients with Alzheimer's disease; and a study to increase ART uptake among HIV
patients in Vietnam. We have shown that methods that lack this clinical link can miss and underestimate high
benefit patients by a factor of 2 or more, compared to even simple methods of this new type.
 In this proposal, we will develop and apply such new clinically-targeted statistical methods for characterizing
high-benefit patients. Such methods will allow physicians and patients to make better choices of best treatments
and programs, with potential to benefit millions of patients. The proposed methods are developed for three aims,
and, following the preliminary work, are motivated by and will be applied to Alzheimer's and HIV studies.
Aim 1. Develop methods to characterize patients who highly benefit from treatment in randomized con-
trolled trials. These methods are significant because they can identify high benefit patients who would be missed
when using standard methods.
Aim 2. Develop methods to characterize patients with high benefit and high risk in randomized trials.
Here, we will develop methods to characterize, patients with high benefit, among those with high risk of an
adverse event. These methods can allow patients to better balance risk and benefit of treatments.
Aim 3. Develop methods to characterize patients who highly benefit from treatment in observational
studies. We will use methods to transform observational studies to a study as close as possible to a randomized
one, where we can then extend the methods of aims 1 and 2. These methods are significant where randomized
trials are not easy to conduct. They will be tested using the above two studies, and also at a PEPFAR (President's
Emerg...

## Key facts

- **NIH application ID:** 10147858
- **Project number:** 5R01AI140854-04
- **Recipient organization:** JOHNS HOPKINS UNIVERSITY
- **Principal Investigator:** CONSTANTINE E FRANGAKIS
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $444,542
- **Award type:** 5
- **Project period:** 2018-05-04 → 2023-04-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10147858

## Citation

> US National Institutes of Health, RePORTER application 10147858, Statistical methods for characterizing patients who highly-benefit from treatments and programs in Alzheimers, HIV, and other heterogeneous diseases (5R01AI140854-04). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10147858. Licensed CC0.

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