Mesothelioma Statistical Model Improves Prognosis Accuracy

Treatment & Doctors
Reading Time: 3 mins
Publication Date: 09/30/2015
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How to Cite’s Article


Povtak, T. (2020, October 16). Mesothelioma Statistical Model Improves Prognosis Accuracy. Retrieved January 30, 2023, from


Povtak, Tim. "Mesothelioma Statistical Model Improves Prognosis Accuracy.", 16 Oct 2020,


Povtak, Tim. "Mesothelioma Statistical Model Improves Prognosis Accuracy." Last modified October 16, 2020.

Doctors may soon be giving pleural mesothelioma surgical patients a much clearer, more precise look at their future, replacing the often muddled, best-guess prognosis they have been providing.

Researchers in Italy are developing a promising statistical model that will offer patients a more definitive understanding of their likely survival times. The model also could be used to improve the personalization of treatments.

“Our model could be easily applied,” thoracic surgeon Dr. Giovanni Leuzzi of the National Cancer Institute in Rome told “We have factors that may be combined into a scoring system to better predict the outcome after surgery.”

Even experienced doctors in the past have struggled to accurately predict survival time. Some pleural mesothelioma patients have survived three, four, five years or more after aggressive surgery, although the majority still live less than 12 months.

Oncologists find it tough to explain why some defy the odds.

“This model may be useful to identify two different groups of [mesothelioma] cancer patients: Those with favorable prognoses and those with poor prognoses,” Leuzzi said.

Factors in the Long-Term Survival Model

The Long-Term Survival Model (LTS) stemmed from a retrospective, multicenter study across Italy that included 468 pleural mesothelioma patients undergoing extrapleural pneumonectomy (EPP) surgery.

A total of 107 patients (22.9 percent) lived at least three years after surgery and were classified as long term survivors. Similar factors in that group of patients were used to build the LTS statistical model.

Those factors included:

  • They were younger (59.7 years vs. 61.4 years)
  • They more likely had epithelioid histology (95.3 percent vs. 78.5 percent)
  • They were less likely to have occupational asbestos exposure (71.6 percent vs. 83 percent)
  • They had a lower median ratio between metastatic and resected lymph nodes.

“Patients can benefit in many ways. The patient will be elucidated by the calculated prognosis,” Leuzzi said. “And the post-surgical treatment may be modified or tailored, according to the prognostic group in which the patient falls.”

Researchers found no difference in those receiving multimodal therapy as opposed to those receiving only one type of treatment.

The five, seven and 10 year survival rate for the LTS Group was 48.6 percent, 31.9 percent, and 22.6 percent, respectively.

Model Leads to Personalized Treatment

Leuzzi believes that by splitting surgical patients into either good or poor prognosis groups, it will help oncologists design better future clinical trials on adjuvant therapy.

It also will help to identify which patients would be better suited for aggressive, follow-up surgery and closer scrutiny, eliminating others who would not benefit from a rigorous therapeutic approach.

“This is very interesting,” he said. “The results are different from previous analyses evaluating the long-term survival of the whole cohort. The findings are preliminary, but we found factors that may be combined into a scoring system that will work much better for patients.”

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