Risk of Chemotherapy Toxicity in Older Patients With Blood Cancer or Non-small Cell Lung Cancer

Prognostic ability of the CARG chemotoxicity calculator in patients newly diagnosed with hematologic malignancy

Time frame: 365 days after first dose of chemotherapy

Predictive ability of the Cancer and Aging Research Group (CARG) Chemo-Toxicity calculator

Time frame: 365 days after first dose of chemotherapy

Predictive ability of Chemo-Toxicity calculator to predict grade 3-5 toxicity

Will fit a Cox regression model for time to toxicity (grades 3-5) containing the baseline chemo-toxicity risk score as the only predictor. The overall ability of the model to distinguish grade 3-5 from grade 1-2 toxicity will be evaluated using Harrell's C-statistic, which can be viewed as a generalization of the area under the curve measurement for receiver operator characteristics (ROC's) curves based on binary outcome data. A 95% confidence interval will be constructed for the C-statistic and if the lower bound is greater than 0.5 (expected value if the risk score is not predictive of toxicity) we will conclude that risk score is significantly able to distinguish between toxicity grades.

Time frame: 365 days after first dose of chemotherapy

Predictive ability of Geriatric Assessment (GA) metrics to predict grade 3-5 toxicity

Will fit a Cox regression model for time to toxicity (grades 3-5) containing the baseline chemo-toxicity risk score as the only predictor. The overall ability of the model to distinguish grade 3-5 from grade 1-2 toxicity will be evaluated using Harrell's C-statistic, which can be viewed as a generalization of the area under the curve measurement for ROC's curves based on binary outcome data. A 95% confidence interval will be constructed for the C-statistic and if the lower bound is greater than 0.5 (expected value if the risk score is not predictive of toxicity) we will conclude that risk score is significantly able to distinguish between toxicity grades.

Time frame: 365 days after first dose of chemotherapy

Association between frailty metrics and relative dose intensity (RDI)

Will explore the relationship of RDI and MAX2 (reduced and prescribed) with clinical and biologic factors of frailty. RDI (\>= 85% versus \[vs.\] \< 85%) will be treated as a continuous and dichotomous variable. The distribution of RDI and MAX2 will be examined graphically and transformed to normality as appropriate. Linear regression for continuous RDI and logistic regression for dichotomized RDI will be used to understand the relationship with RDI and independent variables (e.g. GA scores, age, short physical performance battery \[SPPB\] etc.) Stepwise regression will be used to identify significant clinical and biologic factors (e.g. OSU\_Senescence) that are independently associated with continuous or dichotomized RDI.