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M.D. Martin
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MINI 04 - Clinical Care of Lung Cancer (ID 102)
- Event: WCLC 2015
- Type: Mini Oral
- Track: Treatment of Advanced Diseases - NSCLC
- Presentations: 1
- Moderators:L. Gaspar, V. Westeel
- Coordinates: 9/07/2015, 16:45 - 18:15, Mile High Ballroom 2c-3c
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MINI04.07 - Changes in Skeletal Muscle Index and Body Mass Are Prognostic Factors in First Line Stage IV Non-Small Cell Lung Cancer (NCSCL) Patients (ID 3091)
16:45 - 18:15 | Author(s): M.D. Martin
- Abstract
- Presentation
Background:
Cancer cachexia is a complex metabolic syndrome affecting 60-80% of patients with non-small cell lung cancer (NSCLC). The characteristic involuntary weight loss observed in cachexia is associated with poor outcomes in advanced NSCLC; however, reduced muscle mass may be a more reliable prognostic indicator. In this study, we examine the impact of changes in weight and skeletal muscle index (SMI) in the first 12-weeks of therapy on clinical outcome parameters for front line stage IV NSCLC patients.
Methods:
Cancer cachexia is a complex metabolic syndrome affecting 60-80% of patients with non-small cell lung cancer (NSCLC). The characteristic involuntary weight loss observed in cachexia is associated with poor outcomes in advanced NSCLC; however, reduced muscle mass may be a more reliable prognostic indicator. In this study, we examine the impact of changes in weight and skeletal muscle index (SMI) in the first 12-weeks of therapy on clinical outcome parameters for front line stage IV NSCLC patients.
Results:
119 patients had serial weights available and were included for analysis: 49% were male, median age of males was 71, and females were 63 years; 82% had smoking history. Histology was predominantly adenocarcinoma and squamous (62% and 22%). Median PFS was 159 days, and medial OS was 314 days. Median weights for males at baseline, 6 weeks, and 12 weeks were 77.3, 76.9, and 77.3 kilograms respectively. Median weights for females at baseline, 6 weeks, and 12 weeks were 67.1, 66.7, 65.8 kilograms respectively. Baseline weights were less for women than men (p<0.0007) but the change in weight with time was not significantly different at measured time points. Weight loss of greater than 10.39 pounds in the first six weeks of treatment was strongly associated with inferior outcomes (PFS 2.35 vs. 6.44 months, p=2.02 x 10[-7]; OS 3.96 vs. 15.48 months, p=8.71 x 10[-9]). Persistent weight loss at 12 weeks was also associated with worse outcomes (PFS p=1.72x10[-7 ], OS p= 0.00286). Within this cohort, 41 patients had baseline SMI measured from their CT scans, 27 patients had additional CT-derived SMI available at 6- and 12- weeks. Patients with SMI decrease at 12 weeks of at least 2.6 units (n=9, 33%) had an inferior median PFS compared with those not meeting this threshold (2.79 months vs. 9.75 months p<0.05). In a multivariate analysis, this loss, when adjusted by gender, remained significantly associated with PFS (HR=2.37, p < 0.05).
Conclusion:
This study shows the prognostic value of weight loss for progression on first line chemotherapy as early as six weeks following therapy initiation. This analysis confirms the significant association between weight loss on serial measurements and inferior survival in stage IV NSCLC pts. Additionally, this is the first report of decreasing CT-derived SMI correlating with inferior progression free survival on front line platinum doublet therapy for NSCLC.
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P2.06 - Poster Session/ Screening and Early Detection (ID 219)
- Event: WCLC 2015
- Type: Poster
- Track: Screening and Early Detection
- Presentations: 1
- Moderators:
- Coordinates: 9/08/2015, 09:30 - 17:00, Exhibit Hall (Hall B+C)
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P2.06-012 - A Model Incorporating Clinical, Radiographic, and Biomarker Characteristics Predicts Malignancy in Indeterminate Pulmonary Nodules (ID 2890)
09:30 - 17:00 | Author(s): M.D. Martin
- Abstract
Background:
The high false-positive rate associated with low-dose computed tomography (CT) lung cancer screening results in unnecessary testing, cost, and patient anxiety. We hypothesized that an algorithm incorporating clinical, radiographic, and serum biomarker data would be capable of differentiating benign from malignant pulmonary nodules.
Methods:
An institutional biorepository was used to identify 84 patients with ≤ 2 cm indeterminate pulmonary nodules identified on CT scan, including 50 patients with biopsy-proven, node-negative, non-small cell lung cancer (NSCLC) and 34 patients with benign, non-calcified, solitary pulmonary nodules. Clinical and radiographic data were collected from patient charts and imaging studies. Serum specimens were evaluated in a blinded manner for 55 biomarkers using multiplex immunoassays. Random forest analyses were used to generate a multivariate cross-validation prediction model incorporating clinical, radiographic, and serum biomarker data.
Results:
A total of 84 patients were identified with a median nodule size of 5 mm for benign nodules and 15 mm for NSCLC. Median smoking histories were 21 and 28 pack-years and patient age was 62 and 70 years, respectively. An algorithm incorporating serum biomarker profile (IGFBP-4, IGFBP-5, IL-10, IL-1ra, IL-6, SDF-1alpha, IGF-2), age, sex, BMI, COPD, smoking history, hemoptysis, previous cancer, nodule size, nodule location, spiculation, nodule type, and nodule count provided the optimal performance with a sensitivity 92%, specificity 65%, NPV 85%, and PPV 79%. This model performed with an overall accuracy of 81% with a cross-validated AUC=0.904.
Conclusion:
An algorithm incorporating clinical, radiographic, and serum biomarker characteristics may help differentiate benign from malignant pulmonary nodules. This model is currently being externally validated in a second-site patient cohort.
