Pan-cancer analysis of prognostic metastatic phenotypes

Nicholas G. Zaorsky, Xi Wang, Sara M. Garrett, Eric J. Lehrer, Christine Lin, David J. DeGraff, Daniel E. Spratt, Daniel M. Trifiletti, Amar U. Kishan, Timothy N. Showalter, Henry S. Park, Jonathan T. Yang, Vernon M. Chinchilli, Ming Wang

Research output: Contribution to journalArticlepeer-review

14 Scopus citations


Although cancer is highly heterogeneous, all metastatic cancer is considered American Joint Committee on Cancer (AJCC) Stage IV disease. The purpose of this project was to redefine staging of metastatic cancer. Internal validation of nationally representative patient data from the National Cancer Database (n = 461 357; 2010-2013), and external validation using the Surveillance, Epidemiology and End Results database (n = 106 595; 2014-2015) were assessed using the concordance index for evaluation of survival prediction. A Cox proportional hazards model was used for overall survival by considering identified phenotypes (latent classes) and other confounding variables. Latent class analysis was performed for phenotype identification, where Bayesian information criterion (BIC) and sample-size-adjusted BIC were used to select the optimal number of distinct clusters. Kappa coefficients assessed external cluster validation. Latent class analysis identified five metastatic phenotypes with differences in overall survival (P <.0001): (Stage IVA) nearly exclusive bone-only metastases (n = 59 049, 12.8%; median survival 12.7 months; common in lung, breast and prostate cancers); (IVB) predominant lung metastases (n = 62 491, 13.5%; 11.4 months; common in breast, stomach, kidney, ovary, uterus, thyroid, cervix and soft tissue cancers); (IVC) predominant liver/lung metastases (n = 130 014, 28.2%; 7.0 months; common in colorectum, pancreatic, lung, esophagus and stomach cancers); (IVD) bone/liver/lung metastases predominant over brain (n = 61 004, 13.2%; 5.9 months; common in lung and breast cancers); and (IVE) brain/lung metastases predominant over bone/liver (n = 148 799, 32.3%; 5.7 months; lung cancer and melanoma). Long-term survivors were identified, particularly in Stages IVA-B. A pan-cancer nomogram model to predict survival (STARS: site, tumor, age, race, sex) was created, validated and provides 13% better prognostication than AJCC: 1-month concordance index of 0.67 (95% confidence interval [CI]: 0.66-0.67) vs 0.61 (95% CI: 0.60-0.61). STARS is simple, uses easily accessible variables, better prognosticates survival outcomes and provides a platform to develop novel metastasis-directed clinical trials.

Original languageEnglish (US)
Pages (from-to)132-141
Number of pages10
JournalInternational Journal of Cancer
Issue number1
StatePublished - Jan 1 2022

All Science Journal Classification (ASJC) codes

  • Oncology
  • Cancer Research


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