Purpose To investigate the frailty status in Chinese cancer patients through establishing a novel prediction algorithm. Methods The percentage of frailty in various age groups, locations, and tumor types in Chinese cancer patients was investigated. The prediction capacity of frailty on mortality of Chinese cancer patients was analysed by the frailty index composing of routine laboratory data (FI-LAB) accessible from a blood test and calculated as the ratio of abnormal factors to 22 total variables. The establishment of a novel algorithm, MCP (mortality of cancer patients), to predict the 5-year mortality in Chinese cancer patients was accomplished and the algorithm's prediction capacity was tested in the training and validation sets using receiver operating characteristic (ROC) analysis. Results We found that the risk of death in cancer patients can be successfully identified through FI-LAB. The univariable and multivariable Cox regression were used to evaluate the effect of frailty on death. In the 5-year follow-up, 20.6% of the 2959 participants (age = 55.8 +/- 11.7 years; 43.5% female) died, while the mean FI-LAB score in baseline was 0.23 (standard deviation = 0.13; range = 0-0.73). Frailty (after adjusting for gender, age, and other confounders) directly correlated with an increased risk of death, hazard ratio of 12.67 (95% confidence interval [CI]: 7.19, 22.31), compared to those without frailty. In addition, the MCP algorithm (MCP) = 3.678 x FI-LAB + 1.575 x sex + 1.779 x first tumor node metastasis staging, presented an area under the ROC (AUC) of 0.691 (95% CI: 0.656-0.726) and 0.648 (95% CI: 0.613-0.684) in the training and validation sets, respectively. Conclusion Frailty as defined by FI-LAB was common and indicated a significant death risk in cancer patients. Our novel developed algorithm MCP had a passable prediction capacity on 5-year MCP.