Classifying aging as a treatable condition

Why Classifying Aging as a Treatable Condition Matters for Longevity Research and Policy

Classifying aging as a treatable condition is a question about paperwork that decides real outcomes. Medicine runs on codes, indications, and endpoints. A code tells record systems what to count. An indication tells a regulator what a drug is for. An endpoint tells a trial what counts as success. This page serves the futurism and abundance side of this wiki, and it treats longevity as a policy and research fight. Its argument is that the public quarrel over whether aging is a disease is mostly a quarrel over the wrong word, and that the practical levers sit in codes, indications, and accepted measures of decline.

This page is general information for learning and research, not medical or legal advice.

For the biology of aging, see Aging. For how to read claims about specific interventions, see Evaluating anti-aging claims. For the rate idea behind the goal of defeating aging, see Longevity escape velocity.

The angle in one sentence

The disease label that some longevity advocates wanted has been withdrawn, but the function based wording that replaced it, together with regulator rules on composite outcomes and surrogate endpoints, may be a more usable foothold for aging research than the label itself.

What happened in ICD-11

The International Classification of Diseases is the common language used to record and compare health data across hospitals and countries. For ICD-11, the WHO had proposed including the term old age under code MG2A, a category of symptoms, signs, or clinical findings not elsewhere classified. According to the World Health Organization, this category exists for quality control. It lets coders record unclear statements that physicians write on death certificates or medical records. The category has been in place for 50 years, and old age had replaced its earlier label, senility, because that word had gained a negative connotation.

Clinicians and advocacy groups objected that old age as a diagnosis was ageist and could cause harm. One group proposed frailty as a better defined clinical entity instead. Researchers on the other side wrote that MG2A reflected a shift from chronological to biological age and would encourage therapies aimed at aging mechanisms. After a meeting with the ICD-11 committee in October 2021, the category was retitled Ageing associated decline in intrinsic capacity, and the word pathological in the XT9T extension code for ageing was replaced with biological. The WHO now keeps old age for indexing only, so coders can still be guided when a physician writes it. A mirror of the ICD-11 index lists MG2A under the new title, with entries such as age related frailty and senescence.

Why intrinsic capacity is the overlooked part

It is easy to read the new wording as a defeat for the idea of treating aging. A closer reading suggests otherwise. The WHO defines intrinsic capacity as all the mental and physical capacities a person can draw on, including the ability to walk, think, see, hear, and remember. It also says the level of intrinsic capacity is influenced by diseases, injuries, and age related changes. That is a description of something measurable that can rise or fall. The authors who pushed for the change argued that it moves attention from a static label to a dynamic assessment, with room for prediction and prevention.

A category built on measured decline in walking, thinking, and memory is closer to the language a trial needs than a category built on a birthday. Whether anyone can turn it into an accepted trial outcome is an open research question, not a settled fact.

The regulator side

Coding is only half the story. In the United States a drug is approved for an indication, and the basic regulatory picture is covered on the claims page linked above. What matters here is the list of problems the National Institute on Aging says geroscience drugs raise when sponsors approach the FDA. Geroscience is the field built on the premise that drugs aimed at aging mechanisms could prevent or treat several age related conditions at once. The NIA names three novel issues. The first is defining the indication and context of use, since a drug acting on aging mechanisms might be proposed for very wide use while its balance of risk and benefit differs between people. The second is the use of multiple, composite, or global outcomes, such as all cause mortality or physical disability. The third is the role of biomarkers and surrogate endpoints, because aging mechanisms may take decades to produce clinical effects.

The TAME trial (Targeting Aging with Metformin) is described as a pioneering attempt to work inside these rules. Its planners consulted the FDA and chose a composite endpoint of time to onset of major diseases such as heart attack, stroke, heart failure, cancer, mild cognitive impairment or dementia, or death. A 2022 review reports that the FDA would not accept the trial's biomarker data as the primary basis for approval. The same review points out that a design which waits for diseases to appear cannot test a preventive drug given decades earlier. The status of the trial is tracked on the Longevity escape velocity page.

Surrogate endpoints are the real bottleneck

The FDA sorts surrogate endpoints into candidate, reasonably likely, and validated. A validated surrogate needs strong evidence that changing it predicts a specific clinical benefit, and blood pressure as a stand in for stroke is the FDA's own example. Between 2010 and 2012 the FDA approved 45 percent of new drugs based on a surrogate endpoint. Reasonably likely surrogates can support accelerated approval, which the FDA describes as a program for patients with serious diseases.

This is where classification returns. If faster review paths are tied to serious disease, then a drug meant for people who are aging but not yet diagnosed with anything has no obvious fit. That is an interpretation, not an FDA statement, and it is the kind of gap that policy work could test. A validated measure of aging related decline would let trials run in smaller groups over shorter periods, much as blood pressure did for stroke prevention. Without one, every aging trial must wait for people to get sick.

The spending argument

The Centers for Disease Control and Prevention reports that 90 percent of the nation's 5.3 trillion dollars in annual health care spending goes to people with chronic and mental health conditions. Age is recognized as a primary risk factor for many prominent chronic diseases, including heart disease and cancer. If a classification change and an accepted endpoint made it possible to test interventions that delay several of these diseases together, the payoff would show up where spending is heaviest, in years of very poor health and the end of life. The data on how spending concentrates in those years, and the counterpoint that longer lives can add costs, are covered in Healthy lifespan economics.

The stigma side has a price as well. The WHO reports that ageism is associated with earlier death by 7.5 years, and that in the United States one in every seven dollars spent on the eight most expensive conditions was due to ageism, about 63 billion dollars in total. A label that deepens ageism could raise costs while a better endpoint lowers them. Any honest version of the spending argument has to count both.

Arguments against the disease label

The strongest objections come from geriatric medicine. A Lancet Healthy Longevity editorial listed four. Aging happens to everyone, while a disease affects only some. Aging is varied and partly plastic, so chronological age is a poor marker of risk. Calling aging a disease may worsen ageism. And no intervention has yet been clinically shown to slow the rate of aging in humans. Other critics point to medicalization. If aging is a disease, then simply staying alive makes everyone sick, and older adults could be deprioritized for care. Supporters reply that progeria in children is recognized as a disease, and that obesity gained disease codes because it clusters with other conditions.

Readers who follow debates about labels in mental health will notice a familiar pattern. A diagnostic label can open doors to funding and payment while also changing how a person is seen and treated. The Critical views page covers that wider debate.

Limits of this argument

Several parts of the case are weak or uncertain. No validated surrogate endpoint for aging exists today, so the path described here depends on research that may fail. The claim that intrinsic capacity could become a trial outcome is this page's interpretation, not a position taken by the WHO or the FDA. The accelerated approval point is also an interpretation. The ICD-11 entry was checked through a mirror of the index rather than the WHO browser itself, and code titles can change between releases. Spending figures describe the United States and may not carry over to other health systems. Delaying disease could move costs later rather than remove them. Finally, some researchers argue that the label debate is a distraction and that science can proceed without any reclassification.

What citizens, researchers, and students can do

Policy literacy here means knowing the difference between a code, an indication, and an endpoint, and asking which one a proposal actually changes. Researchers can study whether measures of walking, cognition, vision, hearing, and memory predict later chronic disease well enough to serve as surrogates. Students can trace how one ICD category moved from senility to old age to its current title, and what each change was meant to do. Citizens can follow the ICD proposal platform, where the change to the old age category began as a submitted proposal, and the FDA resources on endpoints cited below.

A concrete research question for readers: could a measured decline in intrinsic capacity serve as an accepted outcome in a trial of an intervention targeting aging, and what evidence would show that slowing that decline predicts fewer heart attacks, strokes, cancers, and cases of dementia?

Discussion questions, essay ideas, and learning related AI prompt ideas

Discussion questions

• Does the word disease matter for funding and payment, or do codes, indications, and endpoints matter more?
• Why might geriatricians and longevity researchers disagree about ICD-11 while wanting the same healthy years for older people?
• Should a regulator approve a drug for people with no diagnosed disease if it delays several diseases at once?

Essay ideas

• Trace the history of ICD category MG2A from senility to old age to its current title and explain what each change was meant to fix.
• Argue for or against intrinsic capacity as a trial outcome for interventions that target aging.
• Compare the health costs of ageism with the possible savings from delaying chronic disease.

Learning related AI prompt ideas

• Explain the difference between a diagnostic code, a drug indication, and a trial endpoint using one example of each.
• Describe the three levels of surrogate endpoints the FDA uses and give a known example of a validated one.
• Help me design a study that tests whether decline in walking speed and memory predicts later chronic disease.
• Summarize the main arguments for and against calling aging a disease, with one source for each side.

See also

• Aging
• Escape velocity
• Longevity policy target
• Healthy lifespan economics
• Evaluating anti-aging claims
• Anti-aging research
• Biomedical gerontology
• Abolishing aging
• Medical ethics
• Epidemiology
• Post-scarcity economy