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

Computerized Histologic Risk Predictor (CHiRP) for Early Stage Lung Cancers
早期肺癌的计算机组织学风险预测器 (CHiRP)
批准号:
10352202
负责人:
Anant Madabhushi
金额:
$16.7万
依托单位国家:
美国
项目类别:
财政年份:
2018
资助国家:
美国
项目状态:
已结题
起止时间:
2018-01-01 至 2022-07-14

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中文摘要
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英文摘要
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 histomorphometry based technologies from the Madabhushi group and who will bring quality management systems and production software standards to help create a pre-commercial CHiRP test.
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An AI-enabled Digital Pathology Platform for Multi-Cancer Diagnosis, Prognosis and Prediction of Therapeutic Benefit
  • 批准号:
    10416206
  • 项目类别:
  • 资助金额:
    $60.3万
  • 财政年份:
    2022
  • 负责人:
    Anant Madabhushi
  • 依托单位:
BLRD Research Career Scientist Award Application
  • 批准号:
    10589239
  • 项目类别:
  • 资助金额:
    $0.0万
  • 财政年份:
    2022
  • 负责人:
    Anant Madabhushi
  • 依托单位:
An AI-enabled Digital Pathology Platform for Multi-Cancer Diagnosis, Prognosis and Prediction of Therapeutic Benefit
  • 批准号:
    10698122
  • 项目类别:
  • 资助金额:
    $55.35万
  • 财政年份:
    2022
  • 负责人:
    Anant Madabhushi
  • 依托单位:
Novel Radiomics for Predicting Response to Immunotherapy for Lung Cancer
  • 批准号:
    10703255
  • 项目类别:
  • 资助金额:
    $0.0万
  • 财政年份:
    2021
  • 负责人:
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  • 依托单位:
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