Prognostic effect of liver metastasis in lung cancer patients with distant metastasis

Abstract

Because the need of clinical prognostic evaluation by specific metastatic organ, we aim to analyze the prognostic factors in lung cancer patients with M1b disease with Surveillance Epidemiology and End-Results database (SEER). This retrospective study evaluated lung cancer patients of adenocarcinoma (AD), squamous cell carcinoma (SQCC), and small cell lung cancer (SCLC) selected from SEER. We provided the prognostic correlates of overall survival (OS) and lung cancer-specific survival (LCSS) in this population. 23,679 eligible patients were included. Bone was the most common metastatic site in AD (63.1%) and SQCC (61.1%), while liver was the most prevalent site (61.9%) in SCLC. Single site metastasis was significantly associated with better outcome compared to multiple sites metastases in all patients. Among patients with single site metastasis, OS and LCSS were longer for AD and SCLC if involving brain or bone, with median survival time of 5 to 7 months, comparing to 3 months if invloving liver (all p-values < 0.001). Similarly, among patients with multiple metastases, better outcomes were observed in AD patients (4 vs 3 months; OS and LCSS, p < 0.001) and SCLC patients (6 vs 4 months; OS, p = 0.017; LCSS, p = 0.023) without liver metastasis compared to those with liver metastasis. In conclusion, we estimated multiple survival outcomes by histology of primary tumor and sites of metastasis. Liver metastasis is found to be the worst prognostic factor for AD and SCLC patients with distant metastasis. More in-depth research is warranted to identify patients who are prone to develop distance metastasis, especially to liver.

Population Modeling of Tumor Kinetics and Overall Survival to Identify Prognostic and Predictive Biomarkers of Efficacy for Durvalumab in Patients With Urothelial Carcinoma

“…Our results suggest that liver metastasis is the most influential and statistically significant covariate for tumor growth. This finding is consistent with recent reports showing that liver metastasis is associated with poor prognosis in various cancers . We also showed that baseline tumor size and IC are the most influential and significant covariates for tumor killing after durvalumab treatment.…”

“…This finding is consistent with recent reports showing that liver metastasis is associated with poor prognosis in various cancers. [13][14][15][16][17] We also Figure 2 Forest plots of covariate effects on k g (a) and k kill (b) estimated from the full covariate tumor kinetic model and survival hazard (c) from the full covariate survival model. Circles represent the calculated percent change in the parameter value from the reference value at the indicated covariate values, using the point estimates of the respective covariate effects; error bars represent the 95% confidence intervals of the covariate effects based on the relative standard error estimates from NONMEM; dashed vertical lines represent the reference value; dotted lines represent the 30% change from reference value.…”

Prognostic value of site-specific metastases in pancreatic adenocarcinoma: A Surveillance Epidemiology and End Results database analysis

“…This is in contrast to lung cancer where prognostic differences have been found according to this parameter[12,13]. …”

Tissue‐specific tumor microenvironments influence responses to immunotherapies

“…Furthermore, data indicating a poor response in patients with liver tumors could be confounded with the aggressive nature of tumors that metastasise to the liver. Some evidence indicates that patients with liver metastases have more metastases in other sites indicating a potentially more advanced stage in the cohort of patients with liver metastases …”

“…Some evidence indicates that patients with liver metastases have more metastases in other sites indicating a potentially more advanced stage in the cohort of patients with liver metastases. 24,58 While the injection of genetically identical tumor lines enabled the specific influence of the tissue of tumor growth to be assessed in our mouse models, it should be acknowledged that differences to the human setting need to be considered when drawing parallels to the clinic. In human cancers, the genetics of tumors in distal sites compared with the primary location, and even within the primary tumor, can be highly heterogeneous.…”