Prognosis for Pneumonic-Type Invasive Mucinous Adenocarcinoma in a Single Lobe on CT: Is It Reasonable to Designate It as Clinical T3?

Lung adenocarcinoma: characteristic radiological presentations

Radiology, mainly computed tomography, has a fundamental role in diagnosis, staging and follow-up of lung adenocarcinoma, the most common type of pulmonary cancer. Within its broad spectrum of presentation, the pathological, clinical and morphological characteristics of this neoplasm allow, in an appropriate clinical context, to suggest certain histological subtypes among which are mucinous adenocarcinoma, lepidic growth adenocarcinoma or associated with cystic lung lesions. The objective of this review is to describe the pathologic, clinical and radiological features of those characteristic forms of lung carcinoma that can be diagnosed radiologically with fair accuracy.

[Construction of a Prognostic Prediction Model of Patients with Pathologic N0 in Resected Invasive Mucinous Adenocarcinoma of the Lung]

BACKGROUND

Invasive mucinous adenocarcinoma (IMA) was a rare and specific type of lung adenocarcinoma, which was often characterized by fewer lymphatic metastases. Therefore, it was difficult to evaluate the prognosis of these tumors based on the existing tumor-node-metastasis (TNM) staging. So, this study aimed to develop Nomograms to predict outcomes of patients with pathologic N0 in resected IMA.

METHODS

According to the inclusion criteria and exclusion criteria, IMA patients with pathologic N0 in The Affiliated Lihuili Hospital of Ningbo University (training cohort, n=78) and Ningbo No.2 Hospital (validation cohort, n=66) were reviewed between July 2012 and May 2017. The prognostic value of the clinicopathological features in the training cohort was analyzed and prognostic prediction models were established, and the performances of models were evaluated. Finally, the validation cohort data was put in for external validation.

RESULTS

Univariate analysis showed that pneumonic type, larger tumor size, mixed mucinous/non-mucinous component, and higher overall stage were significant influence factors of 5-year progression-free survival (PFS) and overall survival (OS). Multivariate analysis further indicated that type of imaging, tumor size, mucinous component were the independent prognostic factors for poor 5-year PFS and OS. Moreover, the 5-year PFS and OS rates were 62.82% and 75.64%, respectively. In subgroups, the survival analysis also showed that the pneumonic type and mixed mucinous/non-mucinous patients had significantly poorer 5-year PFS and OS compared with solitary type and pure mucinous patients, respectively. The C-index of Nomograms with 5-year PFS and OS were 0.815 (95%CI: 0.741-0.889) and 0.767 (95%CI: 0.669-0.865). The calibration curve and decision curve analysis (DCA) of both models showed good predictive performances in both cohorts.

CONCLUSIONS

The Nomograms based on clinicopathological characteristics in a certain extent, can be used as an effective prognostic tool for patients with pathologic N0 after IMA resection.