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Stephen Beech

AI-Powered Cancer Survival Calculator Shows Promising Accuracy, Aids Personalized Prognosis

A new highly accurate cancer survival calculator is being developed using artificial intelligence. MARKUS SPISKE/PEXELS

A new “highly accurate” cancer survival calculator is being developed using artificial intelligence.

The new tool can estimate how long patients with breast, thyroid, and pancreatic cancers have left to live to within months, say American scientists.

The prototype developed with machine learning showed that for each of the three cancer types tested, more factors than the cancer stage significantly influenced patients’ survival.

Currently, estimating survival rates for patients with cancer primarily depends on what stage the disease has reached.

Study lead author Dr. Lauren Janczewski said: “There is a multitude of other factors that may influence a patient’s survival beyond just their staging criteria.

“We sought to develop this Cancer Survival Calculator to provide a more personalized estimate of what patients can expect regarding their cancer prognosis.”

The researchers tested the prototype tool on a nationwide cancer dataset. Initial tests estimated five-year survival for patients with cancers of the breast, thyroid, and pancreas.

A new “highly accurate” cancer survival calculator is being developed using artificial intelligence. COTTONBRO STUDIO/PEXELS

Dr. Janczewski says the study aimed to identify the patient, tumor, and treatment characteristics that most greatly influence patient survival for each cancer type.

After cancer experts recommended characteristics to study, the researchers collected relevant information from patients diagnosed in 2015 and 2017 with breast, thyroid, and pancreatic cancers.

The patients’ records were part of the National Cancer Database (NCDB), which contains records of 72 percent of newly diagnosed cancer cases in the United States.

Three-quarters of the collected data were used to train the machine learning algorithms to recognize patterns between characteristics at diagnosis and patients’ survival at five years, and then to rank the factors with the greatest influence on survival.

With the remaining data, the researchers used statistical methods to test the prototype’s accuracy in estimating survival.

The team included data from more than 250,000 breast cancer patients, 76,624 thyroid cancer patients, and 84,514 pancreatic cancer patients.

The researchers found multiple characteristics specific to patients, tumors, and treatments for all three cancer sites significantly influenced survival.

The top four factors influencing whether patients were alive five years after diagnosis for breast cancer were whether the patient had cancer surgery, the patient’s age at diagnosis, tumor size, and time from diagnosis to treatment.

A new “highly accurate” cancer survival calculator is being developed using artificial intelligence. LUKAS/PEXELS

For thyroid cancer, they were age at diagnosis, tumor size, time to treatment, and lymph node involvement.

And for pancreatic cancer, they were cancer surgery; histology, or microscopic analysis of the cancer, tumor size, and age at diagnosis.

Also found to be important for survival from breast cancer were hormone receptor status, which is part of breast cancer staging, and the presence of Ki-67, a biomarker in breast cancer.

Although some of the predictive factors, such as tumor size, are part of cancer staging, Dr. Janczewski said their results showed that many more factors influence survival for cancer patients beyond their disease stage.

Dr. Janczewski, a general surgical resident at Northwestern University McGaw Medical Centre in Chicago, said their validation testing showed that the calculator was “highly accurate” at estimating cancer survival rates – within nine to 10 months of actual survival.

She said: “The Cancer Survival Calculator differs in several ways from cancer survival estimators already in use.”

It includes specific tumor biomarkers and treatment variables that are known to affect a patient’s estimated prognosis, which Dr. Janczewski said many prior survival calculators lack.

She added: “The dataset used to develop the new calculator, the NCDB, is more comprehensive than other calculators’ datasets.”

The research team plans to make the finalized informational tool available to healthcare practitioners.

The findings are due to be presented at the American College of Surgeons (ACS) annual Clinical Congress in Boston, Massachusetts.

 

Produced in association with SWNS Talker

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