Dataset Information

Stable and discriminating radiomic predictor of recurrence in early stage non-small cell lung cancer: Multi-site study.

ABSTRACT:

Objectives

To evaluate whether combining stability and discriminability criteria in building radiomic classifiers will improve the prognosis of cancer recurrence in early stage non-small cell lung cancer on non-contrast computer tomography (CT).

Materials and methods

CT scans of 610 patients with early stage (IA, IB, IIA) NSCLC from four independent cohorts were evaluated. A total of 350 patients from Cleveland Clinic Foundation and University of Pennsylvania were divided into two equal sets for training (D₁) and validation set (D₂). 80 patients from The Cancer Genome Atlas Lung Adenocarcinoma and Squamous Cell Carcinoma and 195 patients from The Cancer Imaging Archive, were used as independent second (D₃) and third (D₄) validation sets. A linear discriminant analysis (LDA) classifier was built based on the most stable and discriminate features. In addition, a radiomic risk score (RRS) was generated by using least absolute shrinkage and selection operator, Cox regression model to predict time to progression (TTP) following surgery.

Results

A feature selection strategy focusing on both feature discriminability and stability resulted in the classifier having a higher discriminability on validation datasets compared to the discriminability alone criteria in discriminating cancer recurrence (D₂, AUC of 0.75 vs. 0.65; D₃, 0.74 vs. 0.62; D₄, 0.76 vs. 0.63). The RRS generated by most stable-discriminating features was significantly associated with TTP compared to discriminating alone criteria (HR = 1.66, C-index of 0.72 vs. HR = 1.04, C-index of 0.62).

Conclusion

Accounting for both stability and discriminability yielded a more generalizable classifier for predicting cancer recurrence and TTP in early stage NSCLC.

SUBMITTER: Khorrami M

PROVIDER: S-EPMC7141152 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundWe aimed to assess whether recurrence patterns affect survival and to use a multi-state model to predict the prognosis of early stage non-small cell lung cancer in patients who underwent surgical resection.MethodsPatients with early stage non-small cell lung cancer who underwent surgical resection at two tertiary medical centers between 2010 and 2015 were retrospectively analyzed. A multi-state model was employed with one initial state (surgery), two intermediate states (locoregional recurrence, distant metastasis), and one absorbing state (death), comprising five transitions: surgery to locoregional recurrence, surgery to distant metastasis, surgery to death without recurrence, locoregional recurrence to death, and distant metastasis to death. Cox proportional hazards models stratified for these transitions were performed with the risk factors; transition probabilities for each patient were predicted.ResultsA total of 949 patients were identified [median age: 67 years, male: 614 (64.6%)]. Recurrence occurred in 194 (20.4%) patients (locoregional recurrence: 7.3%, distant metastasis: 13.1%). Hazard ratios for distant metastasis after surgery were higher for older age (hazard ratio: 1.03, 95% confidence interval: 1.01-1.06) and adenocarcinoma (hazard ratio: 1.67, 95% confidence interval: 1.06-2.61). Lower lobe location exhibited a higher hazard ratio for death after surgery without recurrence (hazard ratio: 1.59, 95% confidence interval: 1.00-2.53). Stage IIB lung cancer showed a higher probability of transition to distant metastasis after surgery than other stages. Cumulative transition hazards rapidly increased in both recurrence patterns until approximately two years after surgery (locoregional recurrence: 0.052; distant metastasis: 0.104). Patients with distant metastasis were more likely to die within 5 years of surgery than those with locoregional recurrence (6.8% and 2.6%, respectively).ConclusionsWith the multi-state model, risk factors and post-relapse survival probabilities differed between locoregional recurrence and distant metastasis. These findings may enable clinicians to establish personalized follow-up strategies for patients undergoing curative resection for early stage non-small cell lung cancer.