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Updated: Feb 3, 2026

Assessment and Communication for People with Disorders of Consciousness

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Published on: August 1, 2017

Prognostic information for people with MS: Impossible or inevitable?

Christoph Heesen¹, Antonio Scalfari², Ian Galea³

¹MS Day Hospital and Institute of Neuroimmunology and Multiple Sclerosis, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.

Multiple Sclerosis (Houndmills, Basingstoke, England)

|October 17, 2018

Summary

Providing long-term prognosis for multiple sclerosis (MS) patients is crucial but often neglected due to unproven nocebo effects. Future strategies aim to offer evidence-based, individualized prognostic estimates with confidence intervals.

Keywords:

Prognosis patient information risk communication

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Area of Science:

Medicine
Neurology
Medical Prognosis

Background:

Delivering prognostic information in medicine is challenging and often neglected.
A suspected nocebo effect of pessimistic estimates is a key reason, though largely unproven.
Patients with multiple sclerosis (MS) have a significant unmet need for long-term prognostic data.

Purpose of the Study:

To discuss the reasons behind the "blind spot" in physicians' attitudes towards providing prognostic information.
To explore strategies for delivering evidence-based, individualized long-term prognostic estimates in clinical settings.

Main Methods:

This is a viewpoint discussion, not an empirical study.
Identifies reasons for the neglect of prognostic information delivery.
Proposes strategies for future prognostic information delivery.

Main Results:

Physicians' reluctance to provide prognostic information stems largely from the uncertainty of estimates.
The suspected nocebo effect remains largely unproven.
There is a clear need for improved methods to deliver prognostic information.

Conclusions:

Addressing the blind spot in prognostic information delivery requires new strategies.
Tools to identify matching patients from large databases are needed.
Developing evidence-based, individualized prognosis with confidence intervals is a key future direction.