# CHIRP Computerized Histologic Risk Predictor (CHiRP) for Early Stage Lung Cancers

> **NIH NIH R01** · EMORY UNIVERSITY · 2022 · $431,216

## Abstract

SUMMARY: In 2016 a total of 224,390 patients in the US were diagnosed with non-small cell lung cancer
(NSCLC) and 16% of these patients (35,902) were diagnosed as early stage (I and II) and eligible for adjuvant
cytotoxic chemotherapy (adj chemo). However, more than 50% of these patients may have low risk disease and
hence may not receive added benefit from adj chemo, while suffering its side-effects. From an economic
standpoint, unnecessary adj chemo for early stage NSCLC results in a loss of over $35,000 for each quality-
adjusted life year lost. With increased lung cancer screening, we can expect an increase in diagnosis of early
stage NSCLC. Two large completed randomized clinical trials of NSCLC (International Adjuvant Lung Cancer
Trial (IALT) and JBR10) involving surgery with and without adj chemo, only found survival benefit in higher stage
patients (>=Stage III). Unfortunately there are currently no validated predictive companion diagnostic (CDx) tools
to identify (1) which stage II NSCLC are at a lower risk for disease recurrence and hence will not receive
additional benefit from adj chemo and (2) which stage 1A, 1B patients are at elevated risk and hence will benefit?
Extant genomic assays have only been shown to be prognostic (i.e. they predict mortality or recurrence) in early
stage NSCLC, 1–5, but this does not imply they are predictive (i.e. they do not predict treatment response).
 Recently, our group validated the computerized histologic risk predictor (CHiRP), an approach that relies
solely on computer extracted morphologic measurements (e.g. cellular orientation, texture, shape, architecture)
from standard H&E tissue slide images to predict early recurrence in early stage NSCLC. CHiRP has been shown
to be prognostic with an accuracy>85% in three independent clinical cohorts (N=290); higher compared to what
has been previously reported for molecular based prognostic tests. However, to show that CHiRP is predictive,
we need access to randomized clinical trial data involving early stage NSCLC patients treated with surgery and
surgery+ adj chemo. The only two trials that fit these criteria are IALT and JBR10. Since molecular tests are
tissue destructive, validation is more difficult compared to a tissue non-destructive approach like CHiRP; clinical
trial groups are often reluctant to share tissue blocks since it is a valuable resource. For this study we have
obtained preliminary approval for use of the slide images from IALT and JBR10 to establish CHiRP as a
predictive Affordable Precision Medicine (APM) solution.
 This Academic-Industry partnership will leverage long-standing collaborations between (1) the
Madabhushi group at Case Western who bring expertise in computational histomorphometric imaging, (2) the
Velcheti group at the Cleveland Clinic (CCF) with clinical expertise in treatment and management of early stage
NSCLC, and (3) Inspirata Inc., a cancer diagnostics company which has recently licensed a number of
histomorphomet...

## Key facts

- **NIH application ID:** 10692497
- **Project number:** 7R01CA216579-06
- **Recipient organization:** EMORY UNIVERSITY
- **Principal Investigator:** Pingfu Fu
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $431,216
- **Award type:** 7
- **Project period:** 2018-01-01 → 2023-12-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10692497

## Citation

> US National Institutes of Health, RePORTER application 10692497, CHIRP Computerized Histologic Risk Predictor (CHiRP) for Early Stage Lung Cancers (7R01CA216579-06). Retrieved via AI Analytics 2026-05-21 from https://api.ai-analytics.org/grant/nih/10692497. Licensed CC0.

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