What can wage development before and after a G93.3 diagnosis tell us about prognoses for myalgic encephalomyelitis?, 2024, Kielland et al

Abstract:
Prognoses for persons affected by myalgic encephalomyelitis (ME) are rarely studied systematically. Existing studies are often based on smaller samples with unclear inclusion and subjective outcome criteria, and few look at wages as indicators of illness trajectories.

This article considers how ME affects the wages and dependency on public transfers of people affected over time, especially in the period when the welfare authorities investigate eligibility for disability pension.

We matched Norwegian population register data on 8485 working-age individuals diagnosed with G93.3 (postviral fatigue syndrome) from 2009 to 2018 with wage and transfer data and compared male and female cases to control groups.

The G93.3 population's wages fell sharply from around 3 years before diagnosis to 1 year after and stabilized at a low level. Public transfers started increasing several years before diagnosis and stabilized at a high level after. Few of those making no or very low income around the time of the diagnosis resumed earning moderate wages, and only exceptional cases returned to wages corresponding to median wages.

Link | PDF (Social Sciences & Humanities Open, open access)

 

That's a really interesting approach.

I'm surprised there have been so few studies that looked at actual work or higher education outcomes in relation to rehab. Maybe policymakers aren't really that keen to know the answer.

 

This is interesting.
It would be nice if there were a way to take into account the change in wages of those who care for PwME....

 

I've only just started reading this, but what an astonishing study. On the surface it is great methodology, covers the real world beyond clinical trials and focuses on objective outcomes. If it does what it says on the tin, it should prove very important in understanding the impact of the illness, provide powerful evidence for advocacy, and perhaps give us the best estimate yet for recovery/improvement rates.

I need to lie down, but here are a couple of snippets

Looks like a decent sample size (6-8.5k):

Fig. 2. Comparing wage development for working age (18–67 years) men and women with a G93.3 diagnosis between the full sample (N = 6249) and the cohort diagnosed in 2016 (N = 1244).

 

It's not un-useful to arguments about the gender pay gap either!

 

Interesting (and a little depressing) study.

I’m actually suprised more people diagnosed with “postviral fatigue” didn’t fully recover. I couldn’t find anything specific in the article but it doesn’t sound like strict criteria.

Nice to see a critique of the rehabilitation model

Also really impressed by this:

 

@Nightsong

I love your new avatar

 

Looks very interesting. Impressed by the work of Kielland so far.

Some take-away points:

- At the time of diagnosis most of the decline in income (and increase in sick leave benefits and transfers) already occurred. If you look at those years before diagnosis, the effect looks really strong compared to the control group (dashed line):


- Very few patients show significantly improvement in income suggesting the recovery rate is low. For example: "In the 2016 cohort, 57% of the 1524 cases showed no improvement, 38% deteriorated, and only 5% improved somehow over the 3 years studied."

- 415 G93.3 patients had data on following a rehabilitation program. Their wages kept falling one year after the program (they had been falling for several years before that) and stabilised afterwards. It would be interesting if they could compare this with the trajectory patients who did not follow rehabilitation. But as the authors suggest, it already indicates a very low succes rate. "going into treatment and rehabilitation interventions with the explicit goal of fully recovering labor capabilities may incite false hope in people often desperate to return to their former lives. [...] health and welfare providers must address this group with realism."

 

Oh great
A new publication from Tjenesten og MEg, a research project on ME patient's meeting with the health care system in Norway. They are doing a thorough job as researchers who actually get it.
Thread here about the project.

They have written a summary of this study:
Ny publikasjon fra prosjektet Tjenesten og Meg om utvikling av lønnsinntekt og offentlig stønader blant ME-syke

automatic translation:
New publication from the project The Service and ME on the development of wage income and public benefits among ME sufferers

quote:

The article concludes that the results are important for several reasons.

• NAV's ambition to restore ME sufferers' earning capacity through measures and treatment interventions can help to create unrealistic hopes among patients who often have a strong desire for recovery. Within the timeframes we have analyzed - which for parts of the group extends over 10 years - few seem to fully return to paid work, and the general trend is a negative development for most.
  
  
• Profits from existing measures in the form of improved earning capacity thus appear to be low.
  
  
• Annual incidence of G93.3 was increasing in the years for which we had data. This gives further reason to investigate how the public sector can best meet this group.
  
  
• In the absence of an effective treatment for ME, more should be invested in research to meet the patient group as best as possible. While services and interventions for the group are currently costly, in their current form they appear to have improved the earning capacity of only a few patients. The search for new and better treatment options should therefore be strengthened.

 

It all depends however on how reliable those databases are.

- First there is the question of whether the diagnostic code G93.3 really reflects ME/CFS. In past database-studies of this kind we have seen abnormally high prevalence rates that increase in older age groups. Table 4 suggests that this cohort was younger with a mean age of 37 and 68% female predominance. Not sure what N= 42,889 and N= 30,468 refers to, probably the number of observations?

The authors do not report data of the entire cohort from which these ME/CFS were taken, so it's hard to estimate the prevalence rate. They note that Bakken et al. found 1162 cases per year in the same registries which corresponded to a incidence rate of 0.026%. In their less complete 2009- to-2015 sample, Kielland et al. found only 40% of the cases that Bakken found, so incidence was quite low. In short, it seems that the G93.3 diagnoses in Norwegian databases seem different that other registries. Perhaps Norwegian patients can comment on how reliable these registries are?

- Another problem is that there are a lot of incomplete cases, especially if you move further away from the diagnosis year. The trend for the 2016-2018 sample for which they had full data, however, looks the same as for the entire G93.3 sample. The authors also note that patients who fully recovered to no longer need medical care or had enough money to got to private clinics might not be recorded in NPR registries.

 

The decline in income prior to diagnosis is stunning and proves what we knew all along: Many pwME have a delayed diagnosis, despite being very sick. It took me about 3 years 9 months.

 

@PhysiosforME a useful paper regarding rehabilitation outcomes.