“The following are the latest risk figures for PML as a result of being treated with natalizumab. Please note that the embedded slideshow is for health professionals only; if you are not a health professional Biogen-Idec don’t want you to see this presentation. If you are a MSer you should be reading my previous post that has been designed for MSers. There is a change in that Biogen-Idec will only be providing these figures from now on every quarter.
“As of the 3rd December 2014 there have been 517 cases of natalizumab-associated PML; an increase of 22 cases over the previous 3 months. Over 132,600 MSers have been exposed to natalizumab. The following graph demonstrates the number of new PML cases per month seems to be relatively stable, despite a gradual and linear increase in number of exposed MSers. Clearly the ratio is decreasing which indicates that the PML de-risking programme is working; in other words less MSers at risk of PML are staying on the natalizumab. Herein lies the problem; this means that the proportion of JCV-ve MSers on natalizumab is increasing. However the total number of MSers on treatment is used in the denominator to calculate the risk of getting PML. If this denominator is changing by including an increasing proportion of MSers who are not at risk of getting PML it will give a falsely low risk of PML. What we need are monthly updates of the PML risk, by excluding all JCV-ve MSers from the analysis. Unfortunately, Biogen-Idec are unable to access this information, despite them providing the JCV antibody assay free. Why? They don’t have consent from the MSers who are being tested for JCV to use their data in this way.”
“The following ratios are my attempt to explain why I think we are under-estimating the PML risk. At present Biogen-Idec is calculating the PML risk using the top equation. What I would like to see are PML risks calculated using the lower equation.”
“The overall mortality associated with PML was 23% in December; in other words 119 MSers have died as result of PML. Please note that the majority of the PML survivors have a poor functional outcome. You need to keep these figures in context of over 132,600 MSers been treated with natalizumab worldwide with over 381,000 years of natalizumab exposure.”
“Since NHS England gave us permission to switch high-risk natalizumab patients to fingolimod, we are continuing to de-risk our natalizumab-treated population. We are hoping by doing this to prevent anyone at our centre from getting PML. Despite this some MSers are not prepared to stop natalizumab, simply because they are doing so well on the drug.”
“The following is the most important headline data slide for MSers regarding risks based on the three identified PML risk factors:
- JCV serostatus
- Duration of treatment
- Previous exposure to immunosuppression
In addition to this is appears that titres or levels of anti-JCV antibodies also play a role in risk (see below) and this needs to be incorporated into future risk models.”
“We have developed a simple infographic to help you integrate all this information. You can download and print this infographic for your own information.”
Plavina et al. Use of JC virus antibody index to stratify risk of progressive multifocal leukoencephalopathy in natalizumab-treated patients with multiple sclerosis. ENS 2013 Multiple Sclerosis I: Therapeutics
Objectives: In MSers treated with natalizumab, the presence of anti-JCV antibodies (JCV Ab+), prior use of immunosuppressants (IS), and increased duration of natalizumab treatment, especially greater than 2 years, are known risk factors for progressive multifocal leukoencephalopathy (PML). With polyomaviruses, higher levels of antibodies have been correlated with increased viral burden and increased disease risk. It is not known whether JCV Ab levels correlate with PML risk in natalizumab-treated MSers. The objective of this analysis is to examine the association between JCV Ab index (JCV antibody level as measured using the STRATIFY JCV DX Select assay) and PML risk in natalizumab-treated MSers.
Methods: Analyses involved JCV Ab index data from JCV Ab+ MSers enrolled in clinical studies or clinical practice. A cross-sectional analysis of JCV Ab index data from MSers without PML was first performed to assess potential relationships between JCV Ab index and known risk factors (natalizumab treatment duration <=24 vs >24 monthly infusions and prior IS use). P values were calculated using a Wilcoxon rank sum test. The association between JCV Ab index and PML was then assessed using all available longitudinal data. Odds ratios (ORs) were estimated from generalised estimating equations with a logit link. The predicted probabilities were then used to update the current PML risk estimates for JCV Ab+ MSers with high/low Ab index by applying Bayes theorem.
Results: JCV Ab index data were available from 71 natalizumab-treated PML MSers at least 6 months prior to PML diagnosis and from 2522 non-PML JCV Ab+ MSers. JCV Ab index was not found to be associated with number of natalizumab infusions (P=0.39) nor prior IS use (P=0.43), but was significantly associated with PML risk (P<0.001). Estimated ORs were at least 4 for high versus low JCV Ab index in JCV Ab+ MSers. Updated PML risk estimates and longitudinal stability of JCV Ab index will be presented.
Conclusion: Risk of PML in JCV Ab negative natalizumab-treated MSers is very low (0.07 per 1000). In JCV Ab+ MSers who have low JCV Ab index, the risk of PML is several-fold lower than the risk currently attributed to all JCV Ab+ MSers. Utilisation of JCV Ab index allows for further clinically meaningful stratification of PML risk in JCV Ab+ natalizumab-treated MSers.