A Prediction Model for Pathologic N2 Disease in Lung Cancer Patients with a Negative Mediastinum by Positron Emission Tomography

Farjah, Farhood; Lou, Feiran; Sima, Camelia S.; Rusch, Valerie W.; Rizk, Nabil P.

doi:10.1097/jto.0b013e3182992421

Cited by 66 publications

(70 citation statements)

References 33 publications

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“…Recently, the potential benefits of using a prediction models based on radiographic risk factors for nodal disease was demonstrated in a subset of patients with a negative mediastinum by PET. 31,32 Prediction models may lead to better diagnostic accuracy, fewer invasive staging procedures, and less provider-level variability in staging practices while ensuring personalized cancer care.…”

Section: Discussionmentioning

confidence: 99%

Vascular endothelial growth factor C complements the ability of positron emission tomography to predict nodal disease in lung cancer

Farjah

Madtes

Wood

et al. 2015

The Journal of Thoracic and Cardiovascular Surgery

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Objective Vascular endothelial growth factors (VEGFs) C and D are biologically rational markers of nodal disease that could improve the accuracy of lung cancer staging. We hypothesized that these biomarkers would improve the ability of positron emission tomography (PET) to predict nodal disease among patients with suspected or confirmed non–small cell lung cancer (NSCLC). Methods A cross-sectional study (2010–2013) was performed of patients prospectively enrolled in a lung nodule biorepository, staged by computed tomography (CT) and PET, and who underwent pathologic nodal evaluation. Enzyme-linked immunosorbent assay was used to measure biomarker levels in plasma from blood drawn before anesthesia. Likelihood ratio testing was used to compare the following logistic regression prediction models: ModelPET, ModelPET/VEGF-C, ModelPET/VEGF-D, and ModelPET/VEGF-C/VEGF-D. To account for 5 planned pairwise comparisons, P values<.01 were considered significant. Results Among 62 patients (median age, 67 years; 48% men; 87% white; and 84% NSCLC), 58% had fluorodeoxyglucose uptake in hilar and/or mediastinal lymph nodes. The prevalence of pathologically confirmed lymph node metastases was 40%. Comparisons of prediction models revealed the following: ModelPET/VEGF-C versus ModelPET (P = .0069), ModelPET/VEGF-D versus ModelPET (P = .1886), ModelPET/VEGF-C/VEGF-D versus ModelPET (P = .0146), ModelPET/VEGF-C/VEGF-D versus ModelPET/VEGF-C (P = .2818), and ModelPET/VEGF-C/VEGF-D versus ModelPET/VEGF-D (P = .0095). In ModelPET/VEGF-C, higher VEGF-C levels were associated with an increased risk of nodal disease (odds ratio, 2.96; 95% confidence interval, 1.26–6.90). Conclusions Plasma levels of VEGF-C complemented the ability of PET to predict nodal disease among patients with suspected or confirmed NSCLC. VEGF-D did not improve prediction.

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Section: Discussionmentioning

confidence: 99%

Vascular endothelial growth factor C complements the ability of positron emission tomography to predict nodal disease in lung cancer

Farjah

Madtes

Wood

et al. 2015

The Journal of Thoracic and Cardiovascular Surgery

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“…However, no studies have used selection for surgical therapy as their primary outcome [19][20][21][22][23].…”

Section: Commentmentioning

confidence: 99%

A Model to Predict the Use of Surgical Resection for Advanced-Stage Non-Small Cell Lung Cancer Patients

David

Andersen

Beckett

et al. 2017

The Annals of Thoracic Surgery

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“…For patients with pN0, there was a consistent trend toward a survival advantage from examination of more intrapulmonary lymph nodes, but not from examination of hilar or mediastinal nodes. This association was stronger with adjustment for T-category, suggesting a link with the innate risk of nodal metastasis, such risk being higher in more advanced tumors [13,14]. In patients with pN1, the association between mediastinal nodal count and prognosis was also linked with T-category.…”

Section: Commentmentioning

confidence: 99%

Survival Implications of Variation in the Thoroughness of Pathologic Lymph Node Examination in American College of Surgeons Oncology Group Z0030 (Alliance)

Osarogiagbon¹,

Decker

Ballman

et al. 2016

The Annals of Thoracic Surgery

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Background Accurate pathologic nodal staging mandates effective collaboration between surgeons and pathologists. The American College of Surgeons Oncology Group Z0030 trial (ACOSOG Z0030) tightly controlled surgical lymphadenectomy practice, but not pathology examination practice. We tested the survival impact of the thoroughness of pathologic examination (using the number of examined lymph nodes as a surrogate). Methods We re-analyzed the mediastinal lymph node dissection arm of ACOSOG Z0030, using logistic regression and Cox-proportional hazards models. Results Of 513 patients, 435 were pN0, 60 pN1, and 17 pN2. The mean number of mediastinal lymph nodes examined was 13.5, 13.1, and 17.1; station 10 lymph nodes were 2.4, 2.7, and 2.6; station 11–14 nodes were 4.6, 6.1, and 6.7; total lymph nodes were 19.7, 21.3, 25.4 respectively. The pN-category and histology were associated with increased number of examined intrapulmonary lymph nodes. Patients with pN1 had more non-hilar N1 nodes than patients with pN0, those with N2 had more N2 nodes examined than those with pN0 or pN1. Patients with pN0 had better survival with examination of more N1 nodes; those with pN1, had better survival with increased mediastinal nodal examination; the likelihood of discovering N2 disease was significantly associated with increased examination of mediastinal and non-hilar N1 lymph nodes. Conclusions Despite rigorously standardized surgical hilar/mediastinal lymphadenectomy, the number of lymph nodes examined was associated with the likelihood of detecting nodal metastasis, and survival. This may indicate an effect of incomplete pathologic examination.

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A Prediction Model for Pathologic N2 Disease in Lung Cancer Patients with a Negative Mediastinum by Positron Emission Tomography

Abstract: A prediction model for pN2 based on six previously described risk factors has reasonable performance characteristics. Observations from this study may guide prospective, multicenter development and validation of a prediction model for pN2.

Cited by 66 publications

References 33 publications

Vascular endothelial growth factor C complements the ability of positron emission tomography to predict nodal disease in lung cancer

Vascular endothelial growth factor C complements the ability of positron emission tomography to predict nodal disease in lung cancer

A Model to Predict the Use of Surgical Resection for Advanced-Stage Non-Small Cell Lung Cancer Patients

Survival Implications of Variation in the Thoroughness of Pathologic Lymph Node Examination in American College of Surgeons Oncology Group Z0030 (Alliance)

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