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E. Kim
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MO05 - Prognostic and Predictive Biomarkers II (ID 95)
- Event: WCLC 2013
- Type: Mini Oral Abstract Session
- Track: Medical Oncology
- Presentations: 1
- Moderators:J. Hu, S. O'Toole
- Coordinates: 10/28/2013, 16:15 - 17:45, Parkside Auditorium, Level 1
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MO05.06 - DISCUSSANT (ID 3911)
16:40 - 16:55 | Author(s): E. Kim
- Abstract
- Presentation
Abstract not provided
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MO18 - NSCLC - Targeted Therapies IV (ID 116)
- Event: WCLC 2013
- Type: Mini Oral Abstract Session
- Track: Medical Oncology
- Presentations: 1
- Moderators:L. Horn, J. Wolf
- Coordinates: 10/29/2013, 16:15 - 17:45, Bayside Auditorium B, Level 1
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MO18.13 - DISCUSSANT (ID 3959)
17:25 - 17:35 | Author(s): E. Kim
- Abstract
- Presentation
Abstract not provided
Only Members that have purchased this event or have registered via an access code will be able to view this content. To view this presentation, please login, select "Add to Cart" and proceed to checkout. If you would like to become a member of IASLC, please click here.
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P3.06 - Poster Session 3 - Prognostic and Predictive Biomarkers (ID 178)
- Event: WCLC 2013
- Type: Poster Session
- Track: Biology
- Presentations: 1
- Moderators:
- Coordinates: 10/30/2013, 09:30 - 16:30, Exhibit Hall, Ground Level
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P3.06-015 - Integrated Prognosis in Early Stage Resectable Lung Adenocarcinoma (ID 1707)
09:30 - 09:30 | Author(s): E. Kim
- Abstract
Background
Treatment decisions in stage I and II resectable lung adenocarcinoma (ADC) are heterogeneous due to low efficacy of treatment and a high frequency of co-morbidities in the patient population. Currently, pathological stage is the main determinant of adjuvant treatment recommendations. The cell cycle progression (CCP) score is a proliferation based expression profile that has been shown to add significant prognostic stratification within stage I and II patients. We have developed an integrated prognostic model of pathological stage and the CCP expression score in order to maximize the prognostic utility of both markers.Methods
Cox proportional hazards models with pathological stage and the CCP expression score were created from two data sets: 256 patients (190 stage I, 66 stage II) from the Director’s Consortium microarray cohort and 381 adenocarcinomas (337 stage I, 44 stage II) from a clinical study set analyzed by qPCR. Expression microarray data were scaled to adjust for differences in experimental platforms. The primary outcome measure was cancer-specific death, defined as death from lung cancer or death with recurrence within five years of surgery. Coefficients for modeling were derived from the hazard ratio in the Cox PH model.Results
Both pathological stage and CCP score were independent predictors of lung cancer death in both cohorts. The coefficients for pathological stage and CCP score were consistent across both data sets and did not differ significantly between the analysis of all patients and a subset of untreated patients. A combined score (CS) of stage and CCP score (0.33 * CCP score + 0.52 * stage) was created from the subset of untreated patients. When applied to untreated patients in the clinical ADC cohort, pathological stage alone provided estimates of five-year risk of cancer-specific death of 12.6% (stage IA), 22.6% (stage IB), 38.4% (stage IIA) and 60% (stage IIB). In the same cohort, the combined score could separate stage IA patients with five-year risk estimates ranging from 6% to 24%. Similarly increased discrimination of risk estimates were observed for stage IB (10% to 42%), stage IIA (21% to 63%) and stage IIB patients (32% to 75%).Conclusion
A combination of pathological stage and the CCP expression score is a more effective predictor of post-surgical risk of cancer-specific death than either marker alone. A more precise risk assessment provides better guidance in balancing treatment related risks with disease-specific survival.
