Web Calculator Estimates Colorectal Cancer Survival More Accurately

The new tool aims to help patients make more informed treatment decisions and manage expectations following a cancer diagnosis.

A novel web calculator can reliably predict absolute survival rates for men and women with colorectal cancer, a recent study suggests.

The authors of the study, published in BMJ, sought to develop and externally validate risk prediction equations to estimate absolute and conditional survival in patients with colorectal cancer.

A web calculator, called QCancer Colorectal Survival, can be used by both patients and physicians. It is intended to help individuals make more informed decisions regarding treatment and manage expectations following diagnosis, according to the authors.

Furthermore, it provides patients with the ability to update their mortality risk based on their length of survival following a cancer diagnosis.

The web-based tool was developed using the QResearch database, which collects patient data from approximately 1500 general practices across England via the Egton Medical Information Systems clinical computer system.

“Current methods of estimating survival tend to be unreliable and sometimes patients can be given a fairly misleading and unnecessarily gloomy prognosis based only on the grade and stage of their cancer, only to find that in reality they live much longer than these crude predictions when other information is taken into account,” said Julia Hippisley-Cox, co-creator of the tool. “The good news is that this new calculator, which doctors and patients can access, will offer a far more realistic estimate. We understand that not everyone will want to do this, of course, but some patients are very keen on this approach so it’s an individual choice.”

The current methods for predicting patient survival use simple averages based only on age or the grade and stage of the cancer in the wider population, according to the study. The new tool includes additional risk factors, such as smoking history, body mass index, family history, other illnesses and treatments, and information on whether they have had surgery or chemotherapy.

For the study, the investigators used data of more than 44,145 patients from 947 practices to develop separate equations for men and women aged 15 to 99 years with bowel cancer.

The primary outcome of the study was all cause mortality, and the secondary outcome was colorectal cancer mortality.

Next, the investigators tested the equations, using them retrospectively to predict the outcome at 1 year, 5 years, and 10 years after diagnosis for 15,214 patients with bowel cancer from 305 different GP practices and 437,821 colorectal cancer patients from the national cancer registry.

The following variables in men and women were included in the final models: age, deprivation score, cancer stage, cancer grade, smoking status, colorectal surgery, chemotherapy, family history of bowel cancer, raised platelet count, abnormal liver function, cardiovascular disease, diabetes, chronic renal disease, chronic obstructive pulmonary disease, and prescribed aspirin and statins at diagnosis.

Among women, improved survival was associated with earlier stage of cancer, younger age, well or moderately differentiated cancer grade, colorectal cancer surgery, family history of bowel cancer, and prescriptions for statins and aspirin at diagnosis, with comparable results for men, according to the study.

“The risk equations were well calibrated, with predicted risks closely matching observed risks,” the authors wrote. “Discrimination was good in men and women in both validation cohorts.”

In fact, the 5-year survival equations on the QResearch validation cohort explained 45.3% of the variation in time to colorectal cancer death for women, a 1.86 D statistic, and a 0.80 Harrell’s C statistic, according to the study. This means the scores could distinguish between patients with different levels of risk.

“Risk prediction equations were developed and validated to estimate overall and conditional survival of patients with colorectal cancer accounting for an individual’s clinical and demographic characteristics,” the authors concluded. “These equations can provide more individualized accurate information or patients with colorectal cancer to inform decision-making and follow-up.”