Receiving a diagnosis that we have a progressively debilitating disease such as cancer or multiple sclerosis is a lifetime sentence. Initial diagnostic tests can accurately stage the disease. New imaging tools such as PET scans, MRIs, and genetic testing can detect the extent of the disease long spread before it becomes evident to clinicians and much quicker than older techniques such as XRays and CT scans.

Changing the staging of diseases improves life expectancy, but it doesn’t change the outcome for individual patients.

These improved “body microscopes” allow better staging of health problems and the costing of affordable care. Earlier detection and reclassification of the seriousness of a disease may or may not benefit an individual patient. There is lots of evidence both ways, especially in prostate cancer.

One thing is clear however, changing the staging of diseases plays havoc with research data and subsequent funding of treatments. By changing the staging of a disease, research can be shown to improve life expectancy, even though the outcome of individual patients has not changed. Moving sicker people to more severe stages makes the severe stage appear to have better outcomes from the same treatment. At the same time, taking sicker people out of a less severe stage makes that stage appear to have better outcomes too. This phenomenon is euphemistically called stage migration.

Stage immigration can also occur, which is where a new stage creates a new treatment. An expansion in the number of stages in a disease leads to an increase in the numbers of patients treated. Robotic surgery for prostate cancer is one example where the introduction of a precancerous stage leads to the increased use of a simple treatment.

For the individual patient who is moved from a less serious category to a more serious one, it shouldn’t matter, the more accurate the diagnosis, the better the treatment can be planned. But it does. Movement of patients to more serious stages is always accompanied by increased treatment costs. Health insurers both public and private, use these data to make decisions about allocation of funds. They don’t want to have too many patients in very sick categories because the health care costs rise exponentially with severity, usually resulting in a decision to stop payment for the expensive treatments in the more serious stages of the disease.