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Online Tool Helps Predict Survival in ALS

<ѻý class="mpt-content-deck">— Eight-factor model yields AUC of 0.78 for external predictive accuracy
MedpageToday

An online model based on eight variables reliably predicted the personal survival outcome of patients with amyotrophic lateral sclerosis (ALS), European researchers reported.

Based on a study of 11,475 ALS patients from 14 European ALS centers from 1992 to 2016, the model predicted whether patients had very long, long, intermediate, short, or very short times between symptom onset and a composite outcome of noninvasive ventilation for more than 23 hours per day, tracheostomy, or death, according to Leonard van den Berg, MD, PhD, of the University Medical Center Utrecht in the Netherlands, and colleagues.

"We assessed the external validity of our model across several populations, and showed that it had a probability of more than 95% for good performance," they wrote online in the. The model's area under the receiver operator characteristic curve (AUC) concordance statistic for external predictive accuracy was 0.78 and calibration slope was 1.01.

Using baseline clinical, cognitive, and genetic variables defined at diagnosis, the researchers incorporated eight prognostic factors into the model:

  • Bulbar versus nonbulbar onset
  • Age at onset
  • Definite versus probable or possible ALS
  • Diagnostic delay
  • Forced vital capacity
  • Progression rate
  • Frontotemporal dementia
  • Presence of a C9orf72 repeat expansion

The is for physicians only, van den Berg's group stated. Medical doctors must register to obtain access "to minimize the risk of potential harm to patients if the prediction they receive is shorter than expected," they wrote.

While ALS researchers may see the benefits of this model, clinicians should use caution, observed Hiroshi Mitsumoto, MD, of Columbia University Medical Center in New York City in an .

"We do not have strong evidence regarding how to discuss diagnosis and prognosis appropriately and effectively," Mitsumoto wrote. "I believe that some uncertainty and hope are important for patients who have a disease like ALS, and I expect I am not in the minority. When I see patients, I try to find any factors that might be associated with a better prognosis and emphasize these factors."

It's not known whether this statistical prediction tool outperforms expert clinicians, added Bjorn Oskarsson, MD, of the Mayo Clinic in Jacksonville, Florida, who was not involved in the study.

"The predictor tool captures a handful of variables and many less tangible aspects of our patients are not reflected," Oskarsson told ѻý. Factors like psychological well-being and social support aren't incorporated, for example.

It also doesn't account for treatments like riluzole (Rilutek), noninvasive ventilation, and gastrostomy placement. "Presumably, since the patients were all being cared for at multidisciplinary centers of excellence, the use of these interventions was high in the cohort and the application of the model outside of an ALS clinic may not be accurate," he said. And international variations in healthcare practices, including the use of edaravone (Radicut) which is unavailable in Europe, may affect results.

Oskarsson plans to try the tool, but will share only information that's requested and likely to be useful. "Preserving a realistic sense of hope is always important in the face of a terminal disease," he said.

Disclosures

The study was funded by the Netherlands ALS Foundation.

van den Berg disclosed support from the Netherlands ALS Foundation, the Netherlands Organization for Health Research and Development, the EU 7th framework programme for the Euro-MOTOR project, the Netherlands Organization for Health Research and Development, and Baxalta, as well as relevant relationships with Biogen, Cytokinetics, and Baxalta. Co-authors disclosed multiple relevant relationships with industry including Biogen, Baxalta, Mitsubishi-Tanabe, Cytokinetics, GlaxoSmithKline, Orion Pharma, Teva Pfizer, CSL Behring, Treeway, Chronos Therapeutics, and Italfarmaco.

Mitsumoto disclosed relevant relationships with Cytokinetics, Mitsubishi-Tanabe, Denali, and Biohaven.

Primary Source

The Lancet Neurology

Westeneng H-J, et al "Prognosis for patients with amyotrophic lateral sclerosis: development and validation of a personalised prediction model" The Lancet Neurology 2018; DOI:10.1016/S1474-4422(18)30089-9.

Secondary Source

The Lancet Neurology

Mitsumoto H "What if you knew the prognosis of your patients with ALS?" The Lancet Neurology 2018; DOI:10.1016/S1474-4422(18)30111-X.