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FDG-PET SUVmax Combined with IASLC/ATS/ERS Histologic Classification Improves the Prognostic Stratification of Patients with Stage I Lung Adenocarcinoma

  • Thoracic Oncology
  • Published:
Annals of Surgical Oncology Aims and scope Submit manuscript

Abstract

Background

We investigated the association between the newly proposed International Association for the Study of Lung Cancer (IASLC)/American Thoracic Society (ATS)/European Respiratory Society (ERS) classification and 18F-fluorodeoxyglucose (FDG) uptake on positron emission tomography (PET), and whether the combination of these radiologic and pathologic factors can further prognostically stratify patients with stage I lung adenocarcinoma.

Methods

We retrospectively evaluated 222 patients with pathologic stage I lung adenocarcinoma who underwent FDG-PET scanning before undergoing surgical resection between 1999 and 2005. Patients were classified by histologic grade according to the IASLC/ATS/ERS classification (low, intermediate, or high grade) and by maximum standard uptake value (SUVmax) (low <3.0, high ≥3.0). The cumulative incidence of recurrence (CIR) was used to estimate recurrence probabilities.

Results

Patients with high-grade histology had higher risk of recurrence (5-year CIR, 29 % [n = 25]) than those with intermediate-grade (13 % [n = 181]) or low-grade (11 % [n = 16]) histology (p = 0.046). High SUVmax was associated with high-grade histology (p < 0.001) and with increased risk of recurrence compared to low SUVmax (5-year CIR, 21 % [n = 113] vs. 8 % [n = 109]; p = 0.013). Among patients with intermediate-grade histology, those with high SUVmax had higher risk of recurrence than those with low SUVmax (5-year CIR, 19 % [n = 87] vs. 7 % [n = 94]; p = 0.033). SUVmax was associated with recurrence even after adjusting for pathologic stage (p = 0.037).

Conclusions

SUVmax on FDG-PET correlates with the IASLC/ATS/ERS classification and can be used to stratify patients with intermediate-grade histology, the predominant histologic subtype, into two prognostic subsets.

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Acknowledgment

We thank Joe Dycoco for his help with the Thoracic Service lung adenocarcinoma database and Lionel Santibáñez for his editorial assistance. This work was supported in part by the International Association for the Study of Lung Cancer (IASLC)-Young Investigator Award; National Lung Cancer Partnership/LUNGevity Foundation Research grant; Stony Wold-Herbert Fund; American Association for Thoracic Surgery (AATS)-Third Edward D. Churchill Research Scholarship; Mesothelioma Applied Research Foundation (MARF) grant in memory of Lance S. Ruble; William H. Goodwin, and Alice Goodwin, the Commonwealth Foundation for Cancer Research, and the Experimental Therapeutics Center; New York State Empire Clinical Research Investigator Program (ECRIP); the National Cancer Institute (grants U54CA137788, U54CA132378); and the U.S. Department of Defense (grant PR101053).

Disclosure

The authors declare no conflicts of interest.

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Authors and Affiliations

  1. Thoracic Service, Department of Surgery, Memorial Sloan-Kettering Cancer Center, New York, NY, USA

    Kyuichi Kadota MD, PhD, Christos Colovos MD, PhD, Kei Suzuki MD, Nabil P. Rizk MD, Valerie W. Rusch MD & Prasad S. Adusumilli MD

  2. Nuclear Medicine Service, Department of Radiology, Memorial Sloan-Kettering Cancer Center, New York, NY, USA

    Mark P. S. Dunphy DO

  3. Department of Epidemiology and Biostatistics, Memorial Sloan-Kettering Cancer Center, New York, NY, USA

    Emily C. Zabor MS & Camelia S. Sima MD, MS

  4. Department of Pathology, Memorial Sloan-Kettering Cancer Center, New York, NY, USA

    William D. Travis MD

  5. Center for Cell Engineering, Memorial Sloan-Kettering Cancer Center, New York, NY, USA

    Prasad S. Adusumilli MD

  6. Department of Diagnostic Pathology, Faculty of Medicine, Kagawa University, Kagawa, Japan

    Kyuichi Kadota MD, PhD

  7. Department of Laboratory Medicine, Shinshu University Hospital, Matsumoto, Japan

    Akihiko Yoshizawa MD, PhD

Authors
  1. Kyuichi Kadota MD, PhD
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  2. Christos Colovos MD, PhD
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  3. Kei Suzuki MD
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  7. Camelia S. Sima MD, MS
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  8. Akihiko Yoshizawa MD, PhD
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  10. Valerie W. Rusch MD
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  11. Prasad S. Adusumilli MD
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Correspondence to Prasad S. Adusumilli MD.

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Kadota, K., Colovos, C., Suzuki, K. et al. FDG-PET SUVmax Combined with IASLC/ATS/ERS Histologic Classification Improves the Prognostic Stratification of Patients with Stage I Lung Adenocarcinoma. Ann Surg Oncol 19, 3598–3605 (2012). https://doi.org/10.1245/s10434-012-2414-3

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