A Grading System for Invasive Pulmonary Adenocarcinoma: A Proposal From the International Association for the Study of Lung Cancer Pathology Committee.

Abstact

A grading system for pulmonary adenocarcinoma has not been established. The International Association for the Study of Lung Cancer pathology panel evaluated a set of histologic criteria associated with prognosis aimed at establishing a grading system for invasive pulmonary adenocarcinoma.

A multi-institutional study involving multiple cohorts of invasive pulmonary adenocarcinomas was conducted. A cohort of 284 stage I pulmonary adenocarcinomas was used as a training set to identify histologic features associated with patient outcomes (recurrence-free survival [RFS] and overall survival [OS]). Receiver operating characteristic curve analysis was used to select the best model, which was validated (n = 212) and tested (n = 300, including stage I-III) in independent cohorts. Reproducibility of the model was assessed using kappa statistics.

The best model (area under the receiver operating characteristic curve [AUC] = 0.749 for RFS and 0.787 for OS) was composed of a combination of predominant plus high-grade histologic pattern with a cutoff of 20% for the latter. The model consists of the following: grade 1, lepidic predominant tumor; grade 2, acinar or papillary predominant tumor, both with no or less than 20% of high-grade patterns; and grade 3, any tumor with 20% or more of high-grade patterns (solid, micropapillary, or complex gland). Similar results were seen in the validation (AUC = 0.732 for RFS and 0.787 for OS) and test cohorts (AUC = 0.690 for RFS and 0.743 for OS), confirming the predictive value of the model. Interobserver reproducibility revealed good agreement (k = 0.617).

A grading system based on the predominant and high-grade patterns is practical and prognostic for invasive pulmonary adenocarcinoma.

Authors
  • Beasley MB
  • Borczuk A
  • Botling J
  • Brambilla E
  • Bubendorf L
  • Chen G
  • Chou TY
  • Chung JH
  • Cooper WA
  • Dacic S
  • Daigneault JB
  • Ferrari-Light D
  • Hirsch FR
  • Hwang D
  • Jain D
  • Kerr KM
  • Kunitoki K
  • Lantuejoul S
  • Lin D
  • Longshore JW
  • Lopez-Rios F
  • Minami Y
  • Mino-Kenudson M
  • Moreira AL
  • Motoi N
  • Nicholson AG
  • Noguchi M
  • Ocampo PSS
  • Papotti M
  • Pass H
  • Pelosi G
  • Poleri C
  • Rekhtman N
  • Roden AC
  • Russell PA
  • Sholl LM
  • Thunnissen E
  • Travis WD
  • Tsao MS
  • Wistuba II
  • Xia Y
  • Yatabe Y
  • Yoshida A
  • Zhong H
PubMed ID
Appears In
J Thorac Oncol, 2020, 15 (10)