R01CA260889

Optimizing Lung Cancer Screening Nodule Evaluation - Summary

The goal of this project is to optimize the management of screen-detected pulmonary nodules, thus maximizing the benefits of lung cancer screening. Lung cancer is the most common cause of cancer death in the US. To curb the burden of this disease, multiple national organizations recommend lung cancer screening with low-dose computed tomography (LDCT). However, up to one third of screening LDCTs identify pulmonary nodules, but only 1-3% of these are cancers.

Screen-detected pulmonary nodules are then followed-up with additional imaging tests and, in some cases, invasive and potentially harmful procedures. Follow-up and subsequent work-up procedures account for a large portion of screening-associated unnecessary harms and costs. An optimal nodule management algorithm should substantially reduce these harms and provide early cancer detection benefits. However, the optimal management of pulmonary nodules detected during lung cancer screening is currently unknown.

There are differing major guidelines for LDCT screen-detected lung nodule management. Most widely implemented guidelines focus on nodule characteristics to decide the need for and type of follow-up. These guidelines fail to incorporate other key patient factors such as age, sex, smoking history, and comorbidities. Furthermore, additional factors can heavily impact the diagnostic accuracy and harms of nodule management strategies and ultimately, the benefits of lung cancer screening. These include:

1) Risk of lung cancer based on participant and nodule characteristics
2) Cancer aggressiveness
3) Type, sequence, and timing of nodule follow-up
4) Follow-up and biopsy-related complications
5) Competing risks of death (non-lung cancer mortality)
6) Impact of evaluation on quality of life

Furthermore, differences in smoking patterns, lung cancer risk, and comorbidities among diverse race and ethnic groups are not incorporated in current nodule management guidelines.

In this project, we will use simulation modeling to efficiently determine optimal algorithms that consider all the issues listed above. We will build a simulation model, the Multi-Racial and Ethnic Lung Cancer Model (MELCAM), based on a previous modeling framework used by our team to extensively study various aspects of lung cancer control.

The project specific aims are to:

1) Derive and validate MELCAM to simulate the management and subsequent outcomes of screening participants from diverse racial and ethnic backgrounds
2) Use MELCAM to compare existing nodule management protocols in terms of overall and quality-adjusted life-year gains and harms
3) Use MELCAM to generate nodule management algorithm(s) that consider the impact of both nodule and patient factors on cancer risk, screening harms, and life expectancy to optimize the types and timing of follow-up procedures
4) Determine the cost-effectiveness of existing and novel follow-up algorithms

Our study is innovative in applying state-of-the-art modeling techniques and personalized approaches to the optimization of pulmonary nodule management, maximizing the benefits of lung cancer screening in diverse populations.

Icahn School Of Medicine At Mount Sinai

TO IDENTIFY CANCER RISKS AND RISK REDUCTION STRATEGIES, TO IDENTIFY FACTORS THAT CAUSE CANCER IN HUMANS, AND TO DISCOVER AND DEVELOP MECHANISMS FOR CANCER PREVENTION AND PREVENTIVE INTERVENTIONS IN HUMANS. RESEARCH PROGRAMS INCLUDE: (1) CHEMICAL, PHYSICAL AND MOLECULAR CARCINOGENESIS, (2) SCREENING, EARLY DETECTION AND RISK ASSESSMENT, INCLUDING BIOMARKER DISCOVERY, DEVELOPMENT AND VALIDATION, (3) EPIDEMIOLOGY, (4) NUTRITION AND BIOACTIVE FOOD COMPONENTS, (5) IMMUNOLOGY AND VACCINES, (6) FIELD STUDIES AND STATISTICS, (7) CANCER CHEMOPREVENTION AND INTERCEPTION, (8) PRE-CLINICAL AND CLINICAL AGENT DEVELOPMENT, (9) ORGAN SITE STUDIES AND CLINICAL TRIALS, (10) HEALTH-RELATED QUALITY OF LIFE AND PATIENT-CENTERED OUTCOMES, AND (11) SUPPORTIVE CARE AND MANAGEMENT OF SYMPTOMS AND TOXICITIES. SMALL BUSINESS INNOVATION RESEARCH (SBIR) PROGRAM: TO EXPAND AND IMPROVE THE SBIR PROGRAM, TO STIMULATE TECHNICAL INNOVATION, TO INCREASE PRIVATE SECTOR COMMERCIALIZATION OF INNOVATIONS DERIVED FROM FEDERAL RESEARCH AND DEVELOPMENT FUNDING, TO INCREASE SMALL BUSINESS PARTICIPATION IN FEDERAL RESEARCH AND DEVELOPMENT, AND TO FOSTER AND ENCOURAGE PARTICIPATION IN INNOVATION AND ENTREPRENEURSHIP BY WOMEN AND SOCIALLY/ECONOMICALLY DISADVANTAGED PERSONS. SMALL BUSINESS TECHNOLOGY TRANSFER (STTR) PROGRAM: TO STIMULATE AND FOSTER SCIENTIFIC AND TECHNOLOGICAL INNOVATION THROUGH COOPERATIVE RESEARCH AND DEVELOPMENT CARRIED OUT BETWEEN SMALL BUSINESS CONCERNS AND RESEARCH INSTITUTIONS, TO FOSTER TECHNOLOGY TRANSFER THROUGH COOPERATIVE RESEARCH AND DEVELOPMENT BETWEEN SMALL BUSINESS CONCERNS AND RESEARCH INSTITUTIONS, TO INCREASE PRIVATE SECTOR COMMERCIALIZATION OF INNOVATIONS DERIVED FROM FEDERAL RESEARCH AND DEVELOPMENT FUNDING, AND FOSTER PARTICIPATION IN INNOVATION AND ENTREPRENEURSHIP BY WOMEN AND SOCIALLY/ECONOMICALLY DISADVANTAGED PERSONS.

93.393 - Cancer Cause and Prevention Research

National Cancer Institute (NCI) [HHS - NIH]

New York, New York 100296504 United States

Single Zip Code

NIH Research Project Grant (Parent R01 Clinical Trial Not Allowed) (PA-20-185)

Amendment Since initial award the total obligations have increased 364% from $751,936 to $3,489,759.