The Article: Luo, J., Chen, Y., Narsavage, G. L., and Ducatman, A. (2012). Predictors of survival in patients with non-small cell lung cancer. Oncology Nursing Forum, 39(6): 609-616.

Big Idea: Lung cancer remains the leading cause of cancer deaths both in the U.S. and worldwide. Non-small cell lung cancer (NSCLC) makes up 80%-85% of lung cancers. Patients typically present with advanced stages, and the median survival time is 4 to 15 months. Chemotherapy slightly increases five-year survival rates. The authors retrospectively studied several factors of 110 rural-Appalachian hospitalized NSCLC patients’ charts to determine one-year overall survival outcomes.

Survey Says!: The researchers found several significant predictive factors of NSCLC one-year survival including: low BMI, elevated neutrophil counts, elevated platelet counts, and advanced cancer stage.

Quotable: “The current study confirmed that cancer staging and low BMI are powerful predictive factors of survival” (p. 613).

“As with elevated neutrophil counts, elevated platelets also may have inflammatory significance; whether inflammation relates directly to prognosis or is merely associated warrants further exploration” (p. 614).

“The study findings were limited to investigating short-term (one year) lung cancer survival rather than long-term survival outcomes. However, in predicting short-term lung cancer survival, the study results demonstrated significant clinical prognostic factors that could be meaningful in clinical trial research with survival outcomes, clinical care, and related areas for treatment” (p. 614).

So What?: This article is fascinating to me. I learned a lot about already extensively-studied predictors of NCSLC survival as well as about the Charlson Comorbidity Index, or CCI, a validated comorbidity tool that helps weigh the impact of comorbidities on mortality.

NSCLC is a common cancer diagnosis with a relatively poor prognosis. It’s important for oncology professionals to understand predictors of survival – common parameters – in order to create early interventions impacting those predictors.