Clinical trials in the United States and China have shown that a new gene-based test for patients with lung cancer beats standard methods in predicting survival, researchers reported Friday.
The findings, published in the British medical journal The Lancet, should help doctors to make more accurate prognoses and better choices for treatment, the scientists said.
Lung cancer is the most lethal type of the disease worldwide, claiming some 1.4 million lives — more than breast, colon, and prostate cancers combined — each year.
The experimental test measures the activity of 14 genes within cancerous tissue, and is especially effective in assessing a form called non-squamous non-small cell cancer, commonly brought on by tobacco use.
"This has the potential to help hundreds of thousands of people every year to survive longer," said David Jablons, the main architect of the study and a professor at the University of California in San Francisco (UCSF).
Currently, doctors classify early-stage lung cancers by their size, location, and microscopic profile.
Known as staging, this type of assessment guides decisions on the use of supplementary treatment — including chemotherapy — after cancerous tissue is removed.
A more precise prognosis would mean "more people who might benefit from additional therapy could receive it after surgery, before any residual cancer has had a chance to grow," Jablons explained in a statement.
Previous research has shown that chemotherapy given in early-stage lung cancer helps thwart recurrence when there is evidence of lymph node involvement.
The problem, however, is that this especially insidious form of the disease is hard to spot early on.
Only some 30 percent of patients in the United States, for example, are detected in the earliest stage, and even then survival is far from guaranteed — 35 to 45 percent of patients identified with stage-one lung cancer die within five years.
"The prognostic test would address the inability to identify these patients," Jablons said.
In the U.S. trial, the new testing method — designed at UCSF and developed by the California-based company Pinpoint Genomics — used an algorithm to calculate the risk of death after examining the tissue of 361 patients at the UCSF Medical Center as low, medium, or high.
All of these patients had had surgery to treat non-squamous, non-cell lung cancer.
The algorithm was then applied to 433 other patients with the earliest stage of the same type of cancer, and their survival rate was monitored over five years.
The method accurately identified patients with high, intermediate, and low risks of death, the researchers said.
A similar study in China, conducted by the China Clinical Trials Consortium, confirmed the results.
A disclosure notice in The Lancet notes that Jablons and several of the co-authors have paid consultant relationships with Pinpoint Genomics.
Copyright AFP
