New research more accurately predicts survival for melanoma patients
19 April 2017
New research from Melanoma Institute Australia (MIA) will help provide more accurate prognoses for melanoma patients. Using the vast database of patients in MIA’s Melanoma Research Database (known as MRD2), which details the patient’s clinical information and outcomes, researchers have developed conditional survival estimates for Stage III melanoma patients to more accurately predict survival outcomes.
The current staging guidelines, produced by the American Joint Committee on Cancer (AJCC), are used to determine prognosis for a patient. However, they are limited as they only provide information to establish a prognosis at initial diagnosis and do not provide data relevant to patients who return for follow-up. Our research, recently published in the Journal of Clinical Oncology, provides this missing information.
For example, if a patient is diagnosed with Stage IIIC melanoma (advanced lymph node disease with large metastases), we know that they have a worse prognosis than someone diagnosed with Stage IIIA melanoma (advanced lymph node disease with small metastases). But if they survive another five years after they are initially diagnosed, their prognosis improves, and – as our research shows – they, in fact, have the same prognosis as someone with Stage IIIA who has also survived five years after their initial diagnosis.
“The idea of conditional survival is that you’re able to tell patients what their prognosis is at different time points after they have been diagnosed,” explains Professor Richard Scolyer, MIA’s Conjoint Medical Director and study author. “By staying alive a few years after your initial diagnosis, your odds of surviving melanoma are much higher than when you were first diagnosed.”
More accurate estimates of survival can guide patients and their doctors with subsequent follow up and treatment decisions. Given the recent introduction of effective immune and targeted systemic therapies, refining the staging system for patient subgroups is crucial.
“The current staging system only takes into account a small number of variables, although they are the most important predictors of outcome. But we know there are many other factors that also affect outcome,” states study author Dr Lauren Haydu who conducted the research while at MIA.
“We are developing a computer algorithm where we can plug in a whole lot of factors to give patients a more accurate prognosis,” adds Professor Richard Scolyer.