European journal of neurology · 2025
Мониторинг вторичной прогрессирующей активности в НР, несмотря на раннее весьма активное лечение, проведенное в рамках исследования СПАМ.
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Cohen Mikael, Rollot Fabien, Debouverie Marc, Zephir Hélène, Vukusic Sandra, De Seze Jérome, Labauge Pierre, Landes-Chateau Cassandre, Mondot Lydiane, Levraut Michael, Ruet Aurélie, Berger Eric, Laplaud David, Ciron Jonathan, Bourre Bertrand, Le Page Emmanuelle, Papeix Caroline, Thouvenot Eric, Al Khedr Abdullatif, Stankoff Bruno, Pelletier Jean, Maillart Elisabeth, Casez Olivier, Moreau Thibault, Defer Gilles, Clavelou Pierre, Cabre Philippe, Moulin Solène, Neau Jean Philippe, Zedet Mickael, Hankiewicz Karolina, Doghri Inès, Nasr Haifa Ben, Pottier Corinne, Magy Laurent, Boulos Dalia Dimitri, Heinzlef Olivier, Camdessanche Jean Philippe, Coustans Marc, Nifle Chantal, Brassat David, Casey Romain, Lebrun-Frenay Christine, OFSEP and SFSEP study groups
Аннотация
СПРАВОЧНАЯ ИНФОРМАЦИЯ: Данные реального мира свидетельствуют о том, что раннее применение высокоактивных методов лечения (HAT) может снизить риск перехода на вторичные прогрессивные MS (SPMS). Однако нынешние знания о факторах прогнозирования результатов должны быть улучшены. Основная цель этого исследования заключалась в определении факторов, связанных с наличием СМПС у пациентов, проходящих лечение в раннем возрасте после появления MS с помощью HAT. МЕТОДЫ: Ретроспективное многоцентральное исследование, основанное на базе французской базы данных о НР. Пациенты, подавшие заявление 5 через несколько лет после запуска MS, EDS ⩽4, и провел последующие мероприятия >5 Включены годы. Увязка каждого ковариата в исходном режиме со временем с появлением СМПС оценивалась по коэффициентам опасности (ПЗ) в нескорректированных и скорректированных моделях коробок пропорциональных рисков. Результаты: Two thousand two hundred и thirty-seven : средний возраст 31.6 Соотношение мужчин и женщин в разбивке по годам 2.3, и медианная ЕДСС 2.0. Расчетная вероятность достижения СМПС, прогресс, не зависящий от активности рецидива (ИПРА), и прогресс, не зависящий от активности (ПИА) на 10 лет 8%, 22%, и 11%, соответственно. После корректировки мы обнаружили, что пациенты женского пола (HR) 0.64, p = 0.036) имели более низкий риск разработки СМПС. Пожилой возраст, ЭДСС >0 (HR) 7.44, р < 0.001) и перорально в отличие от внутривенного HAT (HR) 1.97, p = 0.003) были в значительной степени связаны с повышенным риском СМПС. Ранние PIRA и PIA предсказывали преобразование в SMS. ВЫВОДЫ: Раннее использование НТС привело к снижению риска разработки СМПС по сравнению с 10 Годы. Внедрение ССЗ до того, как какая-либо остаточная инвалидность будет связана с меньшим риском развития.
Оригинал публикации
Secondary progression activity monitoring in MS despite an early highly active treatment the SPAM study.
BACKGROUND: Real-world data suggest that the early use of highly active therapies (HAT) may reduce the risk of transition to secondary progressive MS (SPMS). However, current knowledge about predictive factors of outcomes needs to be improved. The primary objective of this study was to determine factors associated with the occurrence of SPMS in patients treated early after MS onset with an HAT.
METHODS: Retrospective, multicentric study based on the French MS database. Patients who initiated a HAT within 5 years after MS onset, EDSS ⩽4, and had a follow-up >5 years were included. The association of each covariate at baseline with time to the occurrence of SPMS was quantified by hazard ratios (HRs) in unadjusted and adjusted Cox proportional hazards models.
RESULTS: Two thousand two hundred and thirty-seven patients were included in the analysis: mean age 31.6 years, female/male sex ratio 2.3, and median EDSS 2.0. The estimated probability of reaching SPMS, progression independent of relapse activity (PIRA) and progression independent of activity (PIA) at 10 years was 8%, 22%, and 11%, respectively. After adjustment, we found that female patients (HR 0.64, p = 0.036) had a lower risk of developing SPMS. Older age, EDSS >0 (HR 7.44, p < 0.001), and oral versus intravenous HAT (HR 1.97, p = 0.003) were significantly associated with an increased SPMS risk. Early PIRA and PIA predicted conversion to SPMS.
CONCLUSIONS: Early HAT use resulted in a low risk of developing SPMS over 10 years. Introducing the HAT before any residual disability was associated with a lower risk of progression.
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INTRODUCTION
Preventing the occurrence of secondary progressive multiple sclerosis (SPMS) is one of the main actual challenges in managing multiple sclerosis (MS) patients. Many risk factors, such as age at MS diagnosis, quality of relapse recovery, MRI activity with gadolinium‐enhancing or new T2 lesions, and the precocity of starting a disease‐modifying therapy (DMT), influence the time to develop a progressive course. However, long‐term worsening in disease activity‐free relapsing MS patients is typical and associated with MRI brain atrophy [ 1 , 2 ].
During the last decades, several highly active treatments (HAT) have become available to treat active MS, such as natalizumab, S1P receptor modulators, anti‐CD20, alemtuzumab, or cladribine.
The long‐term impact of the early introduction of HAT on the occurrence of SPMS is challenging to evaluate prospectively. However, real‐world data based on patient registries suggest that the early use of DMT, particularly HAT, may reduce the risk of transition to a progressive course of the disease [ 3 , 4 , 5 ].
Knowledge about predictive factors of long‐term outcomes needs to be improved. The concept of No Evidence of Disease Activity (NEDA), defined by the absence of relapses, EDSS increase, and absence of MRI activity, emerged a few years ago [ 6 ] and represents one of the tools used to evaluate treatment response. Nevertheless, the long‐term predictive value of the NEDA regarding the risk of developing SPMS is controversial [ 7 , 8 ].
The concept of PIRA, which relates to an insidious increase of neurological impairment at the distance of any relapse, in opposition to Relapse‐Associated Worsening (RAW), has been proposed [ 9 , 10 , 11 ]. In daily practice, PIRA could be considered what neurologists believe is the transition to SPMS. The occurrence of PIRA could be linked to chronic active disease [ 12 ], and associated with a worse prognosis. A consensus about the precise definition of PIRA has yet to be reached.
Some authors suggested that Progression Independent of Activity (PIA), adding the absence of focal inflammation measured by conventional brain MRI, should be considered instead of PIRA [ 13 ]. They also considered the lack of reversibility of disability progression along follow‐up.
The objective of the SPAM study (Secondary Progression despite early highly Active treatment in MS) was to determine prognostic factors associated with the risk of transition to SPMS in patients early treated with a HAT.
METHODS
This observational cohort study included MS patients from 38 French centers participating in the French MS database ( Observatoire Français de la Sclérose en Plaques ; OFSEP; www.ofsep.org ) [ 14 ]. Clinical and imaging data were collected for each patient during routine follow‐up visits, using dedicated software, the European Database on Multiple Sclerosis [ 15 ]. These data were collected retrospectively during the first visit and prospectively after that.
Primary objective
The primary objective was to determine the clinical factors associated with the risk of transition to SPMS or demonstration of PIRA in patients with MS treated early with an HAT, using the treatment initiation visit as the study's baseline.
Secondary objectives
Secondary objectives were:
To describe the proportion of patients fulfilling the definition of PIRA and PIA.
To determine clinical and MRI factors associated with the risk of transition to SPMS using the MRI visit performed 12 months after initiating HAT as the rebaseline.
To evaluate the predictive value of PIRA, PIA, and RAW on the risk of transition to SPMS.
To evaluate the predictive value of NEDA status 5 years after initiating HAT on disease outcome.
Patients' selection
Patients with relapsing–remitting MS at baseline and who started a HAT during the first 5 years after MS onset, between April 2007 and December 2022, were included in this study. The 2017 McDonald criteria [ 16 ] were applied to the diagnosis of MS. The patients should have an EDSS score lower or equal to 4 and remain on HAT for at least 12 months. The baseline visit was defined as the HAT initiation date.
The following treatments were considered HAT: natalizumab, fingolimod, cladribine, alemtuzumab, mitoxantrone, and anti‐CD20 (rituximab and ocrelizumab).
Patients could switch to another DMT or remain untreated after the initial HAT treatment period but were excluded if they received an immunosuppressive drug before the HAT (azathioprine, cyclophosphamide, daclizumab, mycophenolate mofetil, and methotrexate).
Outcome measures and risk factors
As predefined by the EDMUS software, the occurrence of SPMS was left at the treating physician's discretion in each center and was confirmed for each case at the time of data analysis.
Brain MRI data was collected 6–12 months after the initiation of HAT therapy and 5 years after the baseline visit. NEDA was defined by the absence of relapses, EDSS increase, and MRI activity between HAT initiation and Year 5. Minimal Evidence of Disease Activity (MEDA) was defined as 1 or 2 new T2 lesions on a follow‐up MRI scan without relapses, according to the definition proposed in previous studies [ 17 , 18 ].
As all the patients had an EDSS lower or equal to 4 at baseline, disability worsening was defined by a 1‐point increase in EDSS compared to baseline, confirmed on a second visit at least 6 months later. If EDSS score raised to 5.5 or above, a sustained 0.5‐point increase was considered for the definition of disability progression. Progression events were determined using a fixed baseline. Disability worsening was classified as RAW when it occurred <30 days before or after a relapse and as PIRA in other cases. RAW and PIRA were classified as early during the first 2 years following HAT initiation and late in other cases.
PIRA was defined as sustained without further return to baseline value along follow‐up and reversible in other cases.
PIA was evaluated in a subgroup of patients for whom a rebaseline MRI scan was available, and a scan was performed after the disability progression event. It was defined by combining sustained PIRA with the absence of focal activity on brain MRI (absence of new/enlarging T2 lesion or gadolinium‐enhancing lesion).
Activity Associated Worsening (AAW) was defined as a disability progression event <30 days after a relapse or in the presence of focal activity on brain MRI (new/enlarging T2 lesion or gadolinium‐enhancing lesion).
DMT withdrawal was defined as a period without receiving a treatment longer than 3 months for daily or monthly administered DMT (natalizumab, fingolimod, and mitoxantrone), more than 9 months for anti‐CD 20 treatments, and more than 15 months after the last treatment course for cladribine and alemtuzumab.
Statistical analysis
Statistical analysis was performed with SAS 9.4 (SAS Inst, Cary, NC, USA) and R software version 4.2.2. A two‐sided p <0.05 was considered statistically significant.
We described the study cohort characteristics using the following descriptive parameters for quantitative variables: mean, median, standard deviation, first and third quartiles, minimum, and maximum. Qualitative variables were represented by frequency and percentages.
For the primary objective analysis, a survival analysis was performed in which the event was the occurrence of SPMS.
The association of each covariate at baseline with time to the occurrence of SPMS was quantified by hazard ratios (HRs) with 95% confidence intervals (CIs) using standard survival analysis methods in unadjusted and adjusted Cox proportional hazards models adjusted for the following variables: gender, age at disease onset, age at HAT initiation, number of relapses during the 2 years preceding HAT, EDSS score, type of first relapse and interval between first and second relapse. The proportionality assumption was tested by a global test based on Schoenfeld residuals analysis [ 19 ] and the graphical and numerical methods of Lin et al. [ 20 ] The multivariate modeling strategy included covariates with a p <0.20 in univariate analysis. The time to the occurrence of SPMS was estimated using Kaplan–Meier curves. The type of DMT over follow‐up and the cumulative number of relapses were considered time‐varying covariates.
For the secondary objectives, the same methodology as the primary analysis was performed to determine the risk factors at rebaseline using MRI parameters associated with SPMS. The rebaseline was defined at a brain MRI date between 6 and 12 months after baseline. Then, in a separate analysis, the impact of PIRA, PIA, RAW, and AAW during follow‐up from baseline on the occurrence of SPMS was provided using Kaplan–Meier curves and a Cox model.
Standard protocol approvals, registrations, and patient consents
All patients enrolled in the OFSEP database provided informed consent for participation and informed consent that their data would be stored and used for research. Data confidentiality and safety were ensured according to the recommendations of the French organization Commission Nationale de l'Informatique et des Libertés (CNIL). OFSEP received approval to store clinical, biological, and imaging data for research purposes. The study did not require any additional procedures by French legislation. OFSEP was registered on ClinicalTrials.gov under NCT02889965 . The SPAM study complies with reference methodology MR004 of the Commission Nationale de l'Informatique et des Libertés and was recorded on the French Health Data Hub (registration id F20220808141711).
RESULTS
Among 72,874 patients in the OFSEP database, 4323 were screened for inclusion in the present study, and 2237 patients could be analyzed (Figure 1 ). The female/male sex ratio was 2.4, and the mean age at HAT initiation ± SD was 31.6 years ± 9.4. Median EDSS was 2.0 (interquartile range [IQR]: 1.0–2.5), and mean disease duration ± standard deviation was 2.1 years ± 1.42. The most prescribed HAT were natalizumab (48.1%), fingolimod (36.2%), and ocrelizumab (13.7%). The disease duration was less than 2 years for 50.9% of the cohort and between 2 and 5 years for 49.1%. The cohort description at baseline is detailed in Table 1 .
Study flowchart.
TABLE 1 Cohort description at the HAT introduction (baseline). Variables Total ( N = 2237) % Gender Men 660 29.5 Women 1577 70.5 Age at baseline Mean ± SD 31.6 ± 9.38 EDSS at baseline Median [Q1–Q3] 2.0 [1.0–2.5] Disease duration (years) Mean ± SD 2.1 ± 1.42 Number of relapses during the 2 years preceding HAT 0 155 6.9 1 609 27.2 2 783 35.0 3+ 690 30.8 Disease modifying therapy Alemtuzumab 1 0.04 Cladribine 15 0.7 Fingolimod 810 36.2 Natalizumab 1075 48.1 Ocrelizumab 306 13.7 Ofatumumab 1 0.04 Rituximab 29 1.3 Prior DMT history Naive 868 38.8 Previously treated 1369 61.2 Last received DMT prior to HAT initiation 1369 Dimethyl fumarate 237 17.3 Glatiramer acetate 260 19.0 Interferon beta 670 48.9 Teriflunomide 202 14.8 Gadolinium‐enhancing lesions on brain baseline MRI (N = 1928) Positive 1159 60.1 Negative 682 35.4 Not available/without injection 87 4.5 Infratentorial lesions (N = 1928) Yes 1342 69.6 No 509 26.4 Not available 77 4.0 Spinal cord lesions ( N = 1250) 1250 Yes 919 73.6 No 173 13.8 Not available 158 12.6 Abbreviations: DMT: disease modifying therapy; HAT, highly active treatment.
Cohort description at the HAT introduction (baseline).
Abbreviations: DMT: disease modifying therapy; HAT, highly active treatment.
Patients were followed for a mean of 5.8 years (range = 1.0–15.4). During the follow‐up, 59.2% of patients remained on their initial HAT.
At the last follow‐up, 98 patients have evolved to SPMS.
Primary objective
The results are presented in Table 2 .
TABLE 2 Primary outcome analysis: Baseline parameters associated with the risk of secondary progressive multiple sclerosis. Total no of patients Univariate analysis Multivariate analysis Non‐adjusted HR CI 95%
p
Adjusted HR CI 95%
p
Gender 2237 Male 1 1 Females 0.67 0.44–1.00
0.050
0.64 0.42–0.97 0.036 Age at baseline (years) 2237
<0.001
<0.001
< 30 1 1 [30–40] 2.38 1.40–4.04
0.001
2.26 1.32–3.86
0.003
[40–50] 4.99 2.89–8.59
<0.001
4.42 2.54–7.67
<0.001
≥50 5.85 2.85–12.00
<0.001
5.51 2.67–11.39
<0.001
Number of relapses during the 2 years preceding HAT initiation 2237 0.099 0.170 0 1 1 1 3.69 0.88–15.43 0.074 4.21 1.00–17.67 0.050 2 2.74 0.66–11.43 0.167 3.20 0.76–13.41 0.112 3+ 2.32 0.56–9.65 0.249 2.94 0.70–12.37 0.141 EDSS 2237
<0.001
0.002
0.0 1 1 [1–3.5] 8.4 2.07–34.10
0.003
7.44 1.82–30.32
<0.001
4.0 49.9 7.03–354.8
<0.001
34.60 4.65–257.5
<0.001
DMT after initial HAT 2237
0.008
0.013
Intravenous HAT 1 1 Injectable HAT N.C ‐ ‐ N.C – – Oral HAT 2.09 1.35–3.23
<0.001
1.97 1.27–3.06
0.003
DMT other than HAT 2.04 0.85–4.89 0.110 1.82 0.74–4.45 0.190 Period without being treated 2.15 1.03–4.49
0.041
2.85 1.35–6.01
0.006
Note: Bold termsrepresent statistically significant analysis. Abbreviations: DMT, disease modifying therapy; HAT, Highly active treatment.
Primary outcome analysis: Baseline parameters associated with the risk of secondary progressive multiple sclerosis.
Note: Bold termsrepresent statistically significant analysis.
Abbreviations: DMT, disease modifying therapy; HAT, Highly active treatment.
The univariate analysis identified several variables associated with the risk of developing SPMS: gender, age at baseline, EDSS, and the type of HAT during the follow‐up.
After adjustment, the analysis confirmed that female gender and younger age at baseline were associated with a lower risk of developing SPMS over follow‐up.
Regarding the EDSS score, patients who had a score between 1 and 3.5 inclusive had an adjusted hazard ratio (HR) of 7.44 for developing SPMS in comparison with the EDSS 0 group (95% CI: 1.82–30.32; p < 0.001). Adjusted HR reached 34.6 (95% CI: 4.65–257.5; p < 0.001) for patients with an EDSS equal to 4.
The DMT route was also statistically associated with the occurrence of SPMS. Patients who received an oral HAT had an adjusted HR of 1.97 (95% CI: 1.27–3.06; p = 0.003) compared to those treated with any intravenous treatment. At least one period without exposure to a DMT also raised the risk of a worse prognosis (adjusted HR: 2.85; 95% CI: 1.35–6.01, p = 0.006).
The number of relapses before HAT initiation was not associated with the long‐term evolution of the disease phenotype ( p > 0.05).
Secondary objectives
The proportion of patients fulfilling the definition of PIRA and PIA in comparison with SPMS
During follow‐up, 348 patients (15.5%) experienced PIRA, among which 155 patients fulfilled the PIA definition; 138 patients (6.2%) and 41 patients (1.8%) experienced AAW and RAW, respectively.
Among patients with PIRA, 234/348 (67.2%) had sustained PIRA, and 114/348 (32.8%) experienced further improvement in disability.
The cumulative probability of developing SPMS, PIA, and PIRA at 10 years was 8%, 11%, and 22%, respectively (Figure 2 ).
Cumulative probabilities of reaching secondary progressive MS (SPMS), Progression Independent of Relapse Activity (PIRA), and Progression Independent of Activity (PIA) during follow‐up.
Factors associated with the risk of developing SPMS at rebaseline visit
Analysis based on the rebaseline visit was conducted on 1618 patients, excluding patients who did not have an available follow‐up scan after 12 months of treatment ( n = 612) and patients who developed SPMS before the rebaseline visit ( n = 7).
The statistical analysis found the same results as in the primary outcome analysis: gender, age, EDSS score, and type of HAT were statistically associated with the risk of developing SPMS. The only additional factor related to the long‐term risk of progression was the cumulative number of relapses during follow‐up for patients experiencing three relapses or more after the rebaseline visit (adjusted HR 3.45, 95% CI 1.53–7.8; p = 0.003) compared with patients without relapses. Regarding brain MRI, no significant difference in the risk of developing SPMS was found according to imaging parameters (presence of new T2 lesion or gadolinium‐enhancing lesions).
Long‐term disease course according to the occurrence of PIRA, PIA, and RAW
Considering them as time‐varying covariates, PIRA (unadjusted HR: 4.52; 95% CI: 3.02–6.76, p < 0.001), AAW (unadjusted HR: 5.88; 95% CI: 3.87–8.93, p < 0.001), and RAW (unadjusted HR: 3.95; 95% CI: 1.99–7.87, p < 0.001) were associated with a higher risk of SPMS as considered by the neurologist.
Considering these variables as fixed covariates at baseline, we found that early PIRA was identified as the factor related to the higher risk of conversion to SPMS (unadjusted HR: 10.49; 95% CI: 6.23–17.66, p < 0.001) as well as late PIRA (HR: 3.04; 95% CI: 1.86–4.96, p < 0.001), compared to patients without PIRA (Figure 3a ). PIA was also associated with an increased risk of developing SPMS (HR: 8.36 95% CI: 5.60–12.48, p < 0.001, Figure 3b ).
Probability of reaching secondary progressive MS depending on PIRA (a) and PIA (b) status.
Conversely, among patients with RAW, both early RAW (HR 4.82, p = 0.007) and late RAW (HR 3.62, p = 0.002) impacted equally the risk of developing SPMS.
Predictive values of NEDA and MEDA
Five years after initiating HAT, 1244 patients' NEDA/MEDA status could be assessed. Among them, 623 (50.1%) reached NEDA, and 300 (24.1%) were classified as having MEDA.
Neither NEDA nor MEDA was associated with the risk of developing SPMS during follow‐up, and NEDA status was not related to the risk of developing PIA either.
DISCUSSION
This study aimed to evaluate the prognostic factors that could predict the occurrence of SPMS in patients treated with an HAT. We explored a large sample of patients, demonstrating that (i) with an early introduction of HAT after MS onset, the occurrence of SPMS at 10 years is <10%, (ii) NEDA and MEDA at 5 years are not predictive of progressive course, and iii/ PIRA and PIA could be used as indicators of MS course, and reflect more accurately disability worsening than the SPMS classification.
Our first finding shows that the global transition risk to SPMS in the studied cohort was low, estimated at 3.8% at 5 years and 8% at 10 years. In comparison, previous publications based on natural history or treated patients reported a median survival time for conversion to SPMS ranging from 21.4 to 32.4 years after diagnosis [ 16 , 21 ]. This is also consistent with a recent study that reported that the risk of SPMS was reduced in patients treated with moderate to high efficacy therapies [ 22 ] and with population‐based analysis, such as the Italian MS registry [ 23 ] and MSBase [ 21 ].
The primary outcome analysis confirmed that some demographical characteristics, like older age and male gender, were associated with a worse prognosis and a higher risk of progressive disease. This has already been reported mainly in various epidemiological studies in the past [ 24 ].
The second finding is the identification of some modifiable risk factors. In our analysis, any residual disability defined by an EDSS score higher than 0 was associated with a significantly higher risk of conversion to SPMS. The concept of a two‐stage disability progression has been reported [ 24 ] suggesting that beyond a given level of disability, usually determined by an EDSS equal to 3.0, MS was characterized by an amnesic process with a consistent evolution toward a worsening of disability. Nevertheless, to the best of our knowledge, this study is the first to demonstrate that any residual disability could significantly influence the risk of SPMS. As several clinical trials showed that HAT was efficient in preventing disability progression in comparison to placebo [ 25 , 26 ] or to platform therapies [ 27 , 28 ], our findings suggest that the initiation of HAT should be considered before any residual disability.
Third, the type of HAT also appeared to influence the long‐term prognosis, with a better outcome for patients who received intravenous HAT (predominantly monoclonal antibodies with natalizumab or intravenous anti‐CD20 therapy) than oral therapies, represented mainly by fingolimod in this cohort. Getting robust and prospective data in real life about the comparative effectiveness of DMT in MS is challenging. However, several observational studies have highlighted the superior efficacy of natalizumab [ 29 ] and anti‐CD20 [ 30 ] over fingolimod. Some treatments, like alemtuzumab and cladribine, were underrepresented in our cohort, mainly because they were unavailable in France at the time of data collection. No conclusion can be drawn about the impact of those molecules on long‐term SPMS conversion.
Finally, any confirmed disability progression during follow‐up was associated with a higher risk of SPMS course, especially for early PIRA and PIA. This emphasizes recent publications about the importance of accurate monitoring of disability for the detection of early PIRA, even if a consensus about an exact definition still must be reached [ 9 , 31 ]. Our results also highlighted that among all patients who experienced at least one PIRA event during follow‐up, only 155 (44.5%) fulfilled the PIA definition, including the absence of focal MRI activity and lack of further improvement of disability. As recently reported in the literature, this finding suggests that PIA should be preferred to PIRA as the most relevant marker of disease progression [ 13 ]. PIA may even be more sensitive without further reversibility. Still, as this determination is only possible at the end of follow‐up, it may be less relevant in the daily practice. Finally, considering that PIRA and PIA definitions are very close to the definition of secondary progression, it suggests that in clinical practice, neurologists may have a propensity to underestimate the frequency of SPMS, leading to a diagnostic lag.
Of note is that the relapse rate before HAT initiation was not statistically associated with the long‐term outcome of our study. However, we found that the persistence of a high relapse activity beyond the rebaseline period resulted in a 3.45‐fold increase in the risk of conversion to SPMS.
The link between relapses and early or long‐term disabilities remains debated in the literature. Some observational studies reported that early relapses were associated with a shorter time to progressive disease onset [ 24 , 32 ]. Still, more recently, it has been suggested that relapses may only affect short or mid‐term rather than long‐term prognosis [ 33 , 34 ].
Regarding imaging, conventional parameters in brain MRI did not contribute to the long‐term prognosis in our analysis. Adding 5‐year follow‐up data showed no correlation between NEDA or MEDA status and long‐term outcomes. Nevertheless, several points about MRI analysis can be discussed in this study. The data regarding rebaseline scans and NEDA status at 5 years was only available for 72% and 55.6% of the cohort, which reduced the analyzed sample size for the statistical analysis. A more standardized and frequent collection of MRI data may have allowed a better characterization of PIA and more precise insights into the prognosis value of imaging.
Additionally, data about spinal cord MRI data were unavailable in many cases. Yet, disposing of those data would have been relevant as the prognostic role of spinal cord lesions has been primarily reported before [ 35 ]. Our dataset did not allow us to analyze T1 and T2 brain lesion volume, brain atrophy, also recognized as a prognostic factor of long‐term outcome [ 36 , 37 ], or the presence of chronic active lesions [ 38 ]. Further analyses will explore additional MRI markers in a future study on this cohort.
Our study has several other limitations. One of the first main points that can be raised is the definition of SPMS, which was left at the discretion of treating physicians. Rather than using a standardized definition like the one proposed by Lorscheider et al. a few years ago [ 39 ] or by other experts [ 40 ], it was preferred because it corresponds to how the OFSEP database collects data. Nevertheless, we asked each participating center to confirm the clinical worsening for each identified patient in the database. If this confirmation could not be obtained, the patient was excluded from the analysis to ensure the data's quality.
It was based on a database in which data are collected realistically. Consequently, the time and condition of acquiring clinical and radiological data were not perfectly standardized. Regarding the EDSS score, some variations may be related to rater variability, as reported in the literature [ 41 ].
Another limitation points out the timing of the initiation of HAT. We included patients treated within the first 5 years after MS onset. Recently, two studies suggested that very early initiation of a DMT, defined by an introduction of treatment within the first 2 years, was associated with a better long‐term outcome [ 42 , 43 ]. We could not confirm this finding in our cohort, as disease duration at the time of HAT initiation did not appear to influence the risk of clinical worsening. However, the mean disease duration in our cohort was 2 years, and more than 60% of our patients had already received another DMT before HAT initiation.
Finally, the statistical analysis about the prognosis value of PIRA and PIA could contain some bias as it used data collected during follow‐up for stratification. However, considering those parameters as time‐dependent variables led to the same findings and conclusions.
The SPAM study revealed that the risk of clinical worsening in patients treated with an HAT early was lower than the expected rates from natural history cohorts, validating the current induction treatment strategy in MS. Male and older patients had a higher risk of progression than other patients. PIRA, PIA, and RAW seem adequate to qualify for MS courses and should be used in clinical practice to evaluate treatment efficiency.
Our study also suggests that monoclonal antibodies may benefit more than other immunosuppressive drugs and that HAT should be initiated before the EDSS score measures residual disability.
AUTHOR CONTRIBUTIONS
Mikael Cohen: Investigation; writing – original draft; writing – review and editing; conceptualization. Fabien Rollot: Conceptualization; methodology; software; formal analysis; writing – review and editing. Marc Debouverie: Investigation; writing – review and editing. Hélène Zephir: Investigation; writing – review and editing. Sandra Vukusic: Investigation; writing – review and editing. Jerome De Seze: Investigation; writing – review and editing. Pierre Labauge: Investigation; writing – review and editing. Cassandre Landes‐Chateau: Investigation; writing – review and editing. Lydiane Mondot: Investigation; writing – review and editing. Michael Levraut: Investigation; writing – review and editing. Aurélie Ruet: Investigation; writing – review and editing. Eric Berger: Investigation; writing – review and editing. David Laplaud: Investigation; writing – review and editing. Jonathan Ciron: Investigation; writing – review and editing. Bertrand Bourre: Investigation; writing – review and editing. Emmanuelle Le Page: Investigation; writing – review and editing. Caroline Papeix: Investigation; writing – review and editing. Eric Thouvenot: Investigation; writing – review and editing. Abdullatif Al Khedr: Investigation; writing – review and editing. Bruno Stankoff: Investigation; writing – review and editing. Jean Pelletier: Investigation; writing – review and editing. Elisabeth Maillart: Investigation; writing – review and editing. Olivier Casez: Investigation; writing – review and editing. Thibault Moreau: Investigation; writing – review and editing. Gilles Defer: Investigation; writing – review and editing. Pierre Clavelou: Investigation; writing – review and editing. Philippe Cabre: Investigation; writing – review and editing. Solène Moulin: Investigation; writing – review and editing. Jean Philippe Neau: Investigation; writing – review and editing. Mickael Zedet: Investigation; writing – review and editing. Karolina Hankiewicz: Investigation; writing – review and editing. Inès Doghri: Investigation; writing – review and editing. Haifa Ben Nasr: Investigation; writing – review and editing. Corinne Pottier: Investigation; writing – review and editing. Laurent Magy: Investigation; writing – review and editing. Dalia Dimitri Boulos: Investigation; writing – review and editing. Olivier Heinzlef: Investigation; writing – review and editing. Jean Philippe Camdessanche: Investigation; writing – review and editing. Marc Coustans: Investigation; writing – review and editing. Chantal Nifle: Investigation; writing – review and editing. David Brassat: Investigation; writing – review and editing. Romain Casey: Conceptualization; methodology; software; formal analysis; writing – review and editing. C Lebrun: Conceptualization; investigation; writing – original draft; writing – review and editing.
FUNDING INFORMATION
This study did not receive any funding.
CONFLICT OF INTEREST STATEMENT
Mikael Cohen has received personal compensation for consulting, serving on a scientific advisory board, speaking, or other activities with Biogen, Merck, Sanofi, Roche, Celgene‐BMS, Janssen, Alexion, Horizon Therapeutics, and Ad Scientiam. Fabien Rollot, Marc Debouverie, Helene Zephir, Jerome de Seze, Eric Berger, David Laplaud, Emmanuelle Le Page, Caroline Papeix, Eric Thouvenot, Abdullatif Al Khedr, Bruno Stankoff, Jean Pelletier, Olivier Casez, Thibault Moreau, Pierre Clavelou, Philippe Cabre, Solene Moulin, Jean Philippe Neau, Karolina Hankiewicz, Ines Doghri, Haifa Ben Nasr, Corinne Pottier, Laurent Magy, Dalia Dimitri, Olivier Heinzlef, Jean Philippe Camdessanche, Marc Coustans, Chantal Nifle, Romain Casey, David Brassat, and Christine Lebrun Frenay have nothing to disclose. Sandra Vukusic has received lecturing fees, travel grants, and research support from Biogen, BMS‐Celgene, Janssen, Merck, Novartis, Roche, Sandoz, and Sanofi‐Genzyme. Pierre Labauge received honoraria/grants from Biogen, Novartis, Sanofi Genzyme, Roche, Novartis, and Merck. Aurélie Ruet received honoraria for meeting speaking from Merck, Alexion, Horizon TH, and Sanofi Genzyme. A Ruet received support for traveling from Biogen, Novartis, and Merck. Her institution received research grants from Biogen, Roche, Sanofi‐Genzyme, and BMS.
Jonathan Ciron has received personal compensation for consulting, serving on a scientific advisory board, speaking, or other activities with Biogen, Novartis, Merck, Sanofi, Roche, BMS, Alexion, Horizon Therapeutics, none related to this study. Bertrand Bourre serves on the scientific advisory board and has received funding for travel and honoraria from Alexion, Biogen, BMS, Horizon, Janssen, Merck, Novartis, Sanofi, and Roche. Elisabeth Maillart reports research support from Biogen and personal fees for lectures and advisory boards from Alexion, Biogen, Horizon, Janssen, Merck, Novartis, Roche, Sanofi, and Teva. Gilles Defer received personal compensation for the scientific advisory board from Biogen, BMS, Novartis, Genzyme, Roche, and Teva Pharmaceutical Industries Ltd. funding for travel and/or speaker honoraria from Merck Serono, Biogen, BMS, Novartis, Roche, Genzyme, and Teva Pharmaceutical Industries Ltd. His institution received grants supporting research for my department from Merck Serono, Biogen, Genzyme, and Novartis. Mickael Zedet reported receiving personal fees from Novartis and Alexion, meeting invitations from Merck, Roche, Sanofi, and Sandoz, and travel expenses from Merk, Sandoz, and Novartis outside the submitted work.
ACKNOWLEDGMENTS
The authors thank Mrs. Senia Belkorche for her help in gathering data, the Observatoire Français de la Sclérose en Plaques (OFSEP, http://www.ofsep.org/fr/ ), which is supported by a grant provided by the French government and administered by the Agence Nationale de la Recherche , within the framework of the “Investments for the Future” program (reference ANR‐10‐COHO‐ 002) and the Eugène Devic EDMUS Foundation against Multiple Sclerosis.
Cohen M, Rollot F, Debouverie M, et al. Secondary progression activity monitoring in MS despite an early highly active treatment the SPAM study. Eur J Neurol. 2025;32:e16583. doi: 10.1111/ene.16583
DATA AVAILABILITY STATEMENT
The individual data from this study can be obtained upon request and after validation from the OFSEP scientific committee.
REFERENCES
Associated Data
Data Availability Statement
The individual data from this study can be obtained upon request and after validation from the OFSEP scientific committee.
Preventing the occurrence of secondary progressive multiple sclerosis (SPMS) is one of the main actual challenges in managing multiple sclerosis (MS) patients. Many risk factors, such as age at MS diagnosis, quality of relapse recovery, MRI activity with gadolinium‐enhancing or new T2 lesions, and the precocity of starting a disease‐modifying therapy (DMT), influence the time to develop a progressive course. However, long‐term worsening in disease activity‐free relapsing MS patients is typical and associated with MRI brain atrophy [ 1 , 2 ].
During the last decades, several highly active treatments (HAT) have become available to treat active MS, such as natalizumab, S1P receptor modulators, anti‐CD20, alemtuzumab, or cladribine.
The long‐term impact of the early introduction of HAT on the occurrence of SPMS is challenging to evaluate prospectively. However, real‐world data based on patient registries suggest that the early use of DMT, particularly HAT, may reduce the risk of transition to a progressive course of the disease [ 3 , 4 , 5 ].
Knowledge about predictive factors of long‐term outcomes needs to be improved. The concept of No Evidence of Disease Activity (NEDA), defined by the absence of relapses, EDSS increase, and absence of MRI activity, emerged a few years ago [ 6 ] and represents one of the tools used to evaluate treatment response. Nevertheless, the long‐term predictive value of the NEDA regarding the risk of developing SPMS is controversial [ 7 , 8 ].
The concept of PIRA, which relates to an insidious increase of neurological impairment at the distance of any relapse, in opposition to Relapse‐Associated Worsening (RAW), has been proposed [ 9 , 10 , 11 ]. In daily practice, PIRA could be considered what neurologists believe is the transition to SPMS. The occurrence of PIRA could be linked to chronic active disease [ 12 ], and associated with a worse prognosis. A consensus about the precise definition of PIRA has yet to be reached.
Some authors suggested that Progression Independent of Activity (PIA), adding the absence of focal inflammation measured by conventional brain MRI, should be considered instead of PIRA [ 13 ]. They also considered the lack of reversibility of disability progression along follow‐up.
The objective of the SPAM study (Secondary Progression despite early highly Active treatment in MS) was to determine prognostic factors associated with the risk of transition to SPMS in patients early treated with a HAT.
METHODS
This observational cohort study included MS patients from 38 French centers participating in the French MS database ( Observatoire Français de la Sclérose en Plaques ; OFSEP; www.ofsep.org ) [ 14 ]. Clinical and imaging data were collected for each patient during routine follow‐up visits, using dedicated software, the European Database on Multiple Sclerosis [ 15 ]. These data were collected retrospectively during the first visit and prospectively after that.
Primary objective
The primary objective was to determine the clinical factors associated with the risk of transition to SPMS or demonstration of PIRA in patients with MS treated early with an HAT, using the treatment initiation visit as the study's baseline.
Secondary objectives
Secondary objectives were:
To describe the proportion of patients fulfilling the definition of PIRA and PIA.
To determine clinical and MRI factors associated with the risk of transition to SPMS using the MRI visit performed 12 months after initiating HAT as the rebaseline.
To evaluate the predictive value of PIRA, PIA, and RAW on the risk of transition to SPMS.
To evaluate the predictive value of NEDA status 5 years after initiating HAT on disease outcome.
Patients' selection
Patients with relapsing–remitting MS at baseline and who started a HAT during the first 5 years after MS onset, between April 2007 and December 2022, were included in this study. The 2017 McDonald criteria [ 16 ] were applied to the diagnosis of MS. The patients should have an EDSS score lower or equal to 4 and remain on HAT for at least 12 months. The baseline visit was defined as the HAT initiation date.
The following treatments were considered HAT: natalizumab, fingolimod, cladribine, alemtuzumab, mitoxantrone, and anti‐CD20 (rituximab and ocrelizumab).
Patients could switch to another DMT or remain untreated after the initial HAT treatment period but were excluded if they received an immunosuppressive drug before the HAT (azathioprine, cyclophosphamide, daclizumab, mycophenolate mofetil, and methotrexate).
Outcome measures and risk factors
As predefined by the EDMUS software, the occurrence of SPMS was left at the treating physician's discretion in each center and was confirmed for each case at the time of data analysis.
Brain MRI data was collected 6–12 months after the initiation of HAT therapy and 5 years after the baseline visit. NEDA was defined by the absence of relapses, EDSS increase, and MRI activity between HAT initiation and Year 5. Minimal Evidence of Disease Activity (MEDA) was defined as 1 or 2 new T2 lesions on a follow‐up MRI scan without relapses, according to the definition proposed in previous studies [ 17 , 18 ].
As all the patients had an EDSS lower or equal to 4 at baseline, disability worsening was defined by a 1‐point increase in EDSS compared to baseline, confirmed on a second visit at least 6 months later. If EDSS score raised to 5.5 or above, a sustained 0.5‐point increase was considered for the definition of disability progression. Progression events were determined using a fixed baseline. Disability worsening was classified as RAW when it occurred <30 days before or after a relapse and as PIRA in other cases. RAW and PIRA were classified as early during the first 2 years following HAT initiation and late in other cases.
PIRA was defined as sustained without further return to baseline value along follow‐up and reversible in other cases.
PIA was evaluated in a subgroup of patients for whom a rebaseline MRI scan was available, and a scan was performed after the disability progression event. It was defined by combining sustained PIRA with the absence of focal activity on brain MRI (absence of new/enlarging T2 lesion or gadolinium‐enhancing lesion).
Activity Associated Worsening (AAW) was defined as a disability progression event <30 days after a relapse or in the presence of focal activity on brain MRI (new/enlarging T2 lesion or gadolinium‐enhancing lesion).
DMT withdrawal was defined as a period without receiving a treatment longer than 3 months for daily or monthly administered DMT (natalizumab, fingolimod, and mitoxantrone), more than 9 months for anti‐CD 20 treatments, and more than 15 months after the last treatment course for cladribine and alemtuzumab.
Statistical analysis
Statistical analysis was performed with SAS 9.4 (SAS Inst, Cary, NC, USA) and R software version 4.2.2. A two‐sided p <0.05 was considered statistically significant.
We described the study cohort characteristics using the following descriptive parameters for quantitative variables: mean, median, standard deviation, first and third quartiles, minimum, and maximum. Qualitative variables were represented by frequency and percentages.
For the primary objective analysis, a survival analysis was performed in which the event was the occurrence of SPMS.
The association of each covariate at baseline with time to the occurrence of SPMS was quantified by hazard ratios (HRs) with 95% confidence intervals (CIs) using standard survival analysis methods in unadjusted and adjusted Cox proportional hazards models adjusted for the following variables: gender, age at disease onset, age at HAT initiation, number of relapses during the 2 years preceding HAT, EDSS score, type of first relapse and interval between first and second relapse. The proportionality assumption was tested by a global test based on Schoenfeld residuals analysis [ 19 ] and the graphical and numerical methods of Lin et al. [ 20 ] The multivariate modeling strategy included covariates with a p <0.20 in univariate analysis. The time to the occurrence of SPMS was estimated using Kaplan–Meier curves. The type of DMT over follow‐up and the cumulative number of relapses were considered time‐varying covariates.
For the secondary objectives, the same methodology as the primary analysis was performed to determine the risk factors at rebaseline using MRI parameters associated with SPMS. The rebaseline was defined at a brain MRI date between 6 and 12 months after baseline. Then, in a separate analysis, the impact of PIRA, PIA, RAW, and AAW during follow‐up from baseline on the occurrence of SPMS was provided using Kaplan–Meier curves and a Cox model.
Standard protocol approvals, registrations, and patient consents
All patients enrolled in the OFSEP database provided informed consent for participation and informed consent that their data would be stored and used for research. Data confidentiality and safety were ensured according to the recommendations of the French organization Commission Nationale de l'Informatique et des Libertés (CNIL). OFSEP received approval to store clinical, biological, and imaging data for research purposes. The study did not require any additional procedures by French legislation. OFSEP was registered on ClinicalTrials.gov under NCT02889965 . The SPAM study complies with reference methodology MR004 of the Commission Nationale de l'Informatique et des Libertés and was recorded on the French Health Data Hub (registration id F20220808141711).
RESULTS
Among 72,874 patients in the OFSEP database, 4323 were screened for inclusion in the present study, and 2237 patients could be analyzed (Figure 1 ). The female/male sex ratio was 2.4, and the mean age at HAT initiation ± SD was 31.6 years ± 9.4. Median EDSS was 2.0 (interquartile range [IQR]: 1.0–2.5), and mean disease duration ± standard deviation was 2.1 years ± 1.42. The most prescribed HAT were natalizumab (48.1%), fingolimod (36.2%), and ocrelizumab (13.7%). The disease duration was less than 2 years for 50.9% of the cohort and between 2 and 5 years for 49.1%. The cohort description at baseline is detailed in Table 1 .
Study flowchart.
TABLE 1 Cohort description at the HAT introduction (baseline). Variables Total ( N = 2237) % Gender Men 660 29.5 Women 1577 70.5 Age at baseline Mean ± SD 31.6 ± 9.38 EDSS at baseline Median [Q1–Q3] 2.0 [1.0–2.5] Disease duration (years) Mean ± SD 2.1 ± 1.42 Number of relapses during the 2 years preceding HAT 0 155 6.9 1 609 27.2 2 783 35.0 3+ 690 30.8 Disease modifying therapy Alemtuzumab 1 0.04 Cladribine 15 0.7 Fingolimod 810 36.2 Natalizumab 1075 48.1 Ocrelizumab 306 13.7 Ofatumumab 1 0.04 Rituximab 29 1.3 Prior DMT history Naive 868 38.8 Previously treated 1369 61.2 Last received DMT prior to HAT initiation 1369 Dimethyl fumarate 237 17.3 Glatiramer acetate 260 19.0 Interferon beta 670 48.9 Teriflunomide 202 14.8 Gadolinium‐enhancing lesions on brain baseline MRI (N = 1928) Positive 1159 60.1 Negative 682 35.4 Not available/without injection 87 4.5 Infratentorial lesions (N = 1928) Yes 1342 69.6 No 509 26.4 Not available 77 4.0 Spinal cord lesions ( N = 1250) 1250 Yes 919 73.6 No 173 13.8 Not available 158 12.6 Abbreviations: DMT: disease modifying therapy; HAT, highly active treatment.
Cohort description at the HAT introduction (baseline).
Abbreviations: DMT: disease modifying therapy; HAT, highly active treatment.
Patients were followed for a mean of 5.8 years (range = 1.0–15.4). During the follow‐up, 59.2% of patients remained on their initial HAT.
At the last follow‐up, 98 patients have evolved to SPMS.
Primary objective
The results are presented in Table 2 .
TABLE 2 Primary outcome analysis: Baseline parameters associated with the risk of secondary progressive multiple sclerosis. Total no of patients Univariate analysis Multivariate analysis Non‐adjusted HR CI 95%
p
Adjusted HR CI 95%
p
Gender 2237 Male 1 1 Females 0.67 0.44–1.00
0.050
0.64 0.42–0.97 0.036 Age at baseline (years) 2237
<0.001
<0.001
< 30 1 1 [30–40] 2.38 1.40–4.04
0.001
2.26 1.32–3.86
0.003
[40–50] 4.99 2.89–8.59
<0.001
4.42 2.54–7.67
<0.001
≥50 5.85 2.85–12.00
<0.001
5.51 2.67–11.39
<0.001
Number of relapses during the 2 years preceding HAT initiation 2237 0.099 0.170 0 1 1 1 3.69 0.88–15.43 0.074 4.21 1.00–17.67 0.050 2 2.74 0.66–11.43 0.167 3.20 0.76–13.41 0.112 3+ 2.32 0.56–9.65 0.249 2.94 0.70–12.37 0.141 EDSS 2237
<0.001
0.002
0.0 1 1 [1–3.5] 8.4 2.07–34.10
0.003
7.44 1.82–30.32
<0.001
4.0 49.9 7.03–354.8
<0.001
34.60 4.65–257.5
<0.001
DMT after initial HAT 2237
0.008
0.013
Intravenous HAT 1 1 Injectable HAT N.C ‐ ‐ N.C – – Oral HAT 2.09 1.35–3.23
<0.001
1.97 1.27–3.06
0.003
DMT other than HAT 2.04 0.85–4.89 0.110 1.82 0.74–4.45 0.190 Period without being treated 2.15 1.03–4.49
0.041
2.85 1.35–6.01
0.006
Note: Bold termsrepresent statistically significant analysis. Abbreviations: DMT, disease modifying therapy; HAT, Highly active treatment.
Primary outcome analysis: Baseline parameters associated with the risk of secondary progressive multiple sclerosis.
Note: Bold termsrepresent statistically significant analysis.
Abbreviations: DMT, disease modifying therapy; HAT, Highly active treatment.
The univariate analysis identified several variables associated with the risk of developing SPMS: gender, age at baseline, EDSS, and the type of HAT during the follow‐up.
After adjustment, the analysis confirmed that female gender and younger age at baseline were associated with a lower risk of developing SPMS over follow‐up.
Regarding the EDSS score, patients who had a score between 1 and 3.5 inclusive had an adjusted hazard ratio (HR) of 7.44 for developing SPMS in comparison with the EDSS 0 group (95% CI: 1.82–30.32; p < 0.001). Adjusted HR reached 34.6 (95% CI: 4.65–257.5; p < 0.001) for patients with an EDSS equal to 4.
The DMT route was also statistically associated with the occurrence of SPMS. Patients who received an oral HAT had an adjusted HR of 1.97 (95% CI: 1.27–3.06; p = 0.003) compared to those treated with any intravenous treatment. At least one period without exposure to a DMT also raised the risk of a worse prognosis (adjusted HR: 2.85; 95% CI: 1.35–6.01, p = 0.006).
The number of relapses before HAT initiation was not associated with the long‐term evolution of the disease phenotype ( p > 0.05).
Secondary objectives
The proportion of patients fulfilling the definition of PIRA and PIA in comparison with SPMS
During follow‐up, 348 patients (15.5%) experienced PIRA, among which 155 patients fulfilled the PIA definition; 138 patients (6.2%) and 41 patients (1.8%) experienced AAW and RAW, respectively.
Among patients with PIRA, 234/348 (67.2%) had sustained PIRA, and 114/348 (32.8%) experienced further improvement in disability.
The cumulative probability of developing SPMS, PIA, and PIRA at 10 years was 8%, 11%, and 22%, respectively (Figure 2 ).
Cumulative probabilities of reaching secondary progressive MS (SPMS), Progression Independent of Relapse Activity (PIRA), and Progression Independent of Activity (PIA) during follow‐up.
Factors associated with the risk of developing SPMS at rebaseline visit
Analysis based on the rebaseline visit was conducted on 1618 patients, excluding patients who did not have an available follow‐up scan after 12 months of treatment ( n = 612) and patients who developed SPMS before the rebaseline visit ( n = 7).
The statistical analysis found the same results as in the primary outcome analysis: gender, age, EDSS score, and type of HAT were statistically associated with the risk of developing SPMS. The only additional factor related to the long‐term risk of progression was the cumulative number of relapses during follow‐up for patients experiencing three relapses or more after the rebaseline visit (adjusted HR 3.45, 95% CI 1.53–7.8; p = 0.003) compared with patients without relapses. Regarding brain MRI, no significant difference in the risk of developing SPMS was found according to imaging parameters (presence of new T2 lesion or gadolinium‐enhancing lesions).
Long‐term disease course according to the occurrence of PIRA, PIA, and RAW
Considering them as time‐varying covariates, PIRA (unadjusted HR: 4.52; 95% CI: 3.02–6.76, p < 0.001), AAW (unadjusted HR: 5.88; 95% CI: 3.87–8.93, p < 0.001), and RAW (unadjusted HR: 3.95; 95% CI: 1.99–7.87, p < 0.001) were associated with a higher risk of SPMS as considered by the neurologist.
Considering these variables as fixed covariates at baseline, we found that early PIRA was identified as the factor related to the higher risk of conversion to SPMS (unadjusted HR: 10.49; 95% CI: 6.23–17.66, p < 0.001) as well as late PIRA (HR: 3.04; 95% CI: 1.86–4.96, p < 0.001), compared to patients without PIRA (Figure 3a ). PIA was also associated with an increased risk of developing SPMS (HR: 8.36 95% CI: 5.60–12.48, p < 0.001, Figure 3b ).
Probability of reaching secondary progressive MS depending on PIRA (a) and PIA (b) status.
Conversely, among patients with RAW, both early RAW (HR 4.82, p = 0.007) and late RAW (HR 3.62, p = 0.002) impacted equally the risk of developing SPMS.
Predictive values of NEDA and MEDA
Five years after initiating HAT, 1244 patients' NEDA/MEDA status could be assessed. Among them, 623 (50.1%) reached NEDA, and 300 (24.1%) were classified as having MEDA.
Neither NEDA nor MEDA was associated with the risk of developing SPMS during follow‐up, and NEDA status was not related to the risk of developing PIA either.
DISCUSSION
This study aimed to evaluate the prognostic factors that could predict the occurrence of SPMS in patients treated with an HAT. We explored a large sample of patients, demonstrating that (i) with an early introduction of HAT after MS onset, the occurrence of SPMS at 10 years is <10%, (ii) NEDA and MEDA at 5 years are not predictive of progressive course, and iii/ PIRA and PIA could be used as indicators of MS course, and reflect more accurately disability worsening than the SPMS classification.
Our first finding shows that the global transition risk to SPMS in the studied cohort was low, estimated at 3.8% at 5 years and 8% at 10 years. In comparison, previous publications based on natural history or treated patients reported a median survival time for conversion to SPMS ranging from 21.4 to 32.4 years after diagnosis [ 16 , 21 ]. This is also consistent with a recent study that reported that the risk of SPMS was reduced in patients treated with moderate to high efficacy therapies [ 22 ] and with population‐based analysis, such as the Italian MS registry [ 23 ] and MSBase [ 21 ].
The primary outcome analysis confirmed that some demographical characteristics, like older age and male gender, were associated with a worse prognosis and a higher risk of progressive disease. This has already been reported mainly in various epidemiological studies in the past [ 24 ].
The second finding is the identification of some modifiable risk factors. In our analysis, any residual disability defined by an EDSS score higher than 0 was associated with a significantly higher risk of conversion to SPMS. The concept of a two‐stage disability progression has been reported [ 24 ] suggesting that beyond a given level of disability, usually determined by an EDSS equal to 3.0, MS was characterized by an amnesic process with a consistent evolution toward a worsening of disability. Nevertheless, to the best of our knowledge, this study is the first to demonstrate that any residual disability could significantly influence the risk of SPMS. As several clinical trials showed that HAT was efficient in preventing disability progression in comparison to placebo [ 25 , 26 ] or to platform therapies [ 27 , 28 ], our findings suggest that the initiation of HAT should be considered before any residual disability.
Third, the type of HAT also appeared to influence the long‐term prognosis, with a better outcome for patients who received intravenous HAT (predominantly monoclonal antibodies with natalizumab or intravenous anti‐CD20 therapy) than oral therapies, represented mainly by fingolimod in this cohort. Getting robust and prospective data in real life about the comparative effectiveness of DMT in MS is challenging. However, several observational studies have highlighted the superior efficacy of natalizumab [ 29 ] and anti‐CD20 [ 30 ] over fingolimod. Some treatments, like alemtuzumab and cladribine, were underrepresented in our cohort, mainly because they were unavailable in France at the time of data collection. No conclusion can be drawn about the impact of those molecules on long‐term SPMS conversion.
Finally, any confirmed disability progression during follow‐up was associated with a higher risk of SPMS course, especially for early PIRA and PIA. This emphasizes recent publications about the importance of accurate monitoring of disability for the detection of early PIRA, even if a consensus about an exact definition still must be reached [ 9 , 31 ]. Our results also highlighted that among all patients who experienced at least one PIRA event during follow‐up, only 155 (44.5%) fulfilled the PIA definition, including the absence of focal MRI activity and lack of further improvement of disability. As recently reported in the literature, this finding suggests that PIA should be preferred to PIRA as the most relevant marker of disease progression [ 13 ]. PIA may even be more sensitive without further reversibility. Still, as this determination is only possible at the end of follow‐up, it may be less relevant in the daily practice. Finally, considering that PIRA and PIA definitions are very close to the definition of secondary progression, it suggests that in clinical practice, neurologists may have a propensity to underestimate the frequency of SPMS, leading to a diagnostic lag.
Of note is that the relapse rate before HAT initiation was not statistically associated with the long‐term outcome of our study. However, we found that the persistence of a high relapse activity beyond the rebaseline period resulted in a 3.45‐fold increase in the risk of conversion to SPMS.
The link between relapses and early or long‐term disabilities remains debated in the literature. Some observational studies reported that early relapses were associated with a shorter time to progressive disease onset [ 24 , 32 ]. Still, more recently, it has been suggested that relapses may only affect short or mid‐term rather than long‐term prognosis [ 33 , 34 ].
Regarding imaging, conventional parameters in brain MRI did not contribute to the long‐term prognosis in our analysis. Adding 5‐year follow‐up data showed no correlation between NEDA or MEDA status and long‐term outcomes. Nevertheless, several points about MRI analysis can be discussed in this study. The data regarding rebaseline scans and NEDA status at 5 years was only available for 72% and 55.6% of the cohort, which reduced the analyzed sample size for the statistical analysis. A more standardized and frequent collection of MRI data may have allowed a better characterization of PIA and more precise insights into the prognosis value of imaging.
Additionally, data about spinal cord MRI data were unavailable in many cases. Yet, disposing of those data would have been relevant as the prognostic role of spinal cord lesions has been primarily reported before [ 35 ]. Our dataset did not allow us to analyze T1 and T2 brain lesion volume, brain atrophy, also recognized as a prognostic factor of long‐term outcome [ 36 , 37 ], or the presence of chronic active lesions [ 38 ]. Further analyses will explore additional MRI markers in a future study on this cohort.
Our study has several other limitations. One of the first main points that can be raised is the definition of SPMS, which was left at the discretion of treating physicians. Rather than using a standardized definition like the one proposed by Lorscheider et al. a few years ago [ 39 ] or by other experts [ 40 ], it was preferred because it corresponds to how the OFSEP database collects data. Nevertheless, we asked each participating center to confirm the clinical worsening for each identified patient in the database. If this confirmation could not be obtained, the patient was excluded from the analysis to ensure the data's quality.
It was based on a database in which data are collected realistically. Consequently, the time and condition of acquiring clinical and radiological data were not perfectly standardized. Regarding the EDSS score, some variations may be related to rater variability, as reported in the literature [ 41 ].
Another limitation points out the timing of the initiation of HAT. We included patients treated within the first 5 years after MS onset. Recently, two studies suggested that very early initiation of a DMT, defined by an introduction of treatment within the first 2 years, was associated with a better long‐term outcome [ 42 , 43 ]. We could not confirm this finding in our cohort, as disease duration at the time of HAT initiation did not appear to influence the risk of clinical worsening. However, the mean disease duration in our cohort was 2 years, and more than 60% of our patients had already received another DMT before HAT initiation.
Finally, the statistical analysis about the prognosis value of PIRA and PIA could contain some bias as it used data collected during follow‐up for stratification. However, considering those parameters as time‐dependent variables led to the same findings and conclusions.
The SPAM study revealed that the risk of clinical worsening in patients treated with an HAT early was lower than the expected rates from natural history cohorts, validating the current induction treatment strategy in MS. Male and older patients had a higher risk of progression than other patients. PIRA, PIA, and RAW seem adequate to qualify for MS courses and should be used in clinical practice to evaluate treatment efficiency.
Our study also suggests that monoclonal antibodies may benefit more than other immunosuppressive drugs and that HAT should be initiated before the EDSS score measures residual disability.
AUTHOR CONTRIBUTIONS
Mikael Cohen: Investigation; writing – original draft; writing – review and editing; conceptualization. Fabien Rollot: Conceptualization; methodology; software; formal analysis; writing – review and editing. Marc Debouverie: Investigation; writing – review and editing. Hélène Zephir: Investigation; writing – review and editing. Sandra Vukusic: Investigation; writing – review and editing. Jerome De Seze: Investigation; writing – review and editing. Pierre Labauge: Investigation; writing – review and editing. Cassandre Landes‐Chateau: Investigation; writing – review and editing. Lydiane Mondot: Investigation; writing – review and editing. Michael Levraut: Investigation; writing – review and editing. Aurélie Ruet: Investigation; writing – review and editing. Eric Berger: Investigation; writing – review and editing. David Laplaud: Investigation; writing – review and editing. Jonathan Ciron: Investigation; writing – review and editing. Bertrand Bourre: Investigation; writing – review and editing. Emmanuelle Le Page: Investigation; writing – review and editing. Caroline Papeix: Investigation; writing – review and editing. Eric Thouvenot: Investigation; writing – review and editing. Abdullatif Al Khedr: Investigation; writing – review and editing. Bruno Stankoff: Investigation; writing – review and editing. Jean Pelletier: Investigation; writing – review and editing. Elisabeth Maillart: Investigation; writing – review and editing. Olivier Casez: Investigation; writing – review and editing. Thibault Moreau: Investigation; writing – review and editing. Gilles Defer: Investigation; writing – review and editing. Pierre Clavelou: Investigation; writing – review and editing. Philippe Cabre: Investigation; writing – review and editing. Solène Moulin: Investigation; writing – review and editing. Jean Philippe Neau: Investigation; writing – review and editing. Mickael Zedet: Investigation; writing – review and editing. Karolina Hankiewicz: Investigation; writing – review and editing. Inès Doghri: Investigation; writing – review and editing. Haifa Ben Nasr: Investigation; writing – review and editing. Corinne Pottier: Investigation; writing – review and editing. Laurent Magy: Investigation; writing – review and editing. Dalia Dimitri Boulos: Investigation; writing – review and editing. Olivier Heinzlef: Investigation; writing – review and editing. Jean Philippe Camdessanche: Investigation; writing – review and editing. Marc Coustans: Investigation; writing – review and editing. Chantal Nifle: Investigation; writing – review and editing. David Brassat: Investigation; writing – review and editing. Romain Casey: Conceptualization; methodology; software; formal analysis; writing – review and editing. C Lebrun: Conceptualization; investigation; writing – original draft; writing – review and editing.
FUNDING INFORMATION
This study did not receive any funding.
CONFLICT OF INTEREST STATEMENT
Mikael Cohen has received personal compensation for consulting, serving on a scientific advisory board, speaking, or other activities with Biogen, Merck, Sanofi, Roche, Celgene‐BMS, Janssen, Alexion, Horizon Therapeutics, and Ad Scientiam. Fabien Rollot, Marc Debouverie, Helene Zephir, Jerome de Seze, Eric Berger, David Laplaud, Emmanuelle Le Page, Caroline Papeix, Eric Thouvenot, Abdullatif Al Khedr, Bruno Stankoff, Jean Pelletier, Olivier Casez, Thibault Moreau, Pierre Clavelou, Philippe Cabre, Solene Moulin, Jean Philippe Neau, Karolina Hankiewicz, Ines Doghri, Haifa Ben Nasr, Corinne Pottier, Laurent Magy, Dalia Dimitri, Olivier Heinzlef, Jean Philippe Camdessanche, Marc Coustans, Chantal Nifle, Romain Casey, David Brassat, and Christine Lebrun Frenay have nothing to disclose. Sandra Vukusic has received lecturing fees, travel grants, and research support from Biogen, BMS‐Celgene, Janssen, Merck, Novartis, Roche, Sandoz, and Sanofi‐Genzyme. Pierre Labauge received honoraria/grants from Biogen, Novartis, Sanofi Genzyme, Roche, Novartis, and Merck. Aurélie Ruet received honoraria for meeting speaking from Merck, Alexion, Horizon TH, and Sanofi Genzyme. A Ruet received support for traveling from Biogen, Novartis, and Merck. Her institution received research grants from Biogen, Roche, Sanofi‐Genzyme, and BMS.
Jonathan Ciron has received personal compensation for consulting, serving on a scientific advisory board, speaking, or other activities with Biogen, Novartis, Merck, Sanofi, Roche, BMS, Alexion, Horizon Therapeutics, none related to this study. Bertrand Bourre serves on the scientific advisory board and has received funding for travel and honoraria from Alexion, Biogen, BMS, Horizon, Janssen, Merck, Novartis, Sanofi, and Roche. Elisabeth Maillart reports research support from Biogen and personal fees for lectures and advisory boards from Alexion, Biogen, Horizon, Janssen, Merck, Novartis, Roche, Sanofi, and Teva. Gilles Defer received personal compensation for the scientific advisory board from Biogen, BMS, Novartis, Genzyme, Roche, and Teva Pharmaceutical Industries Ltd. funding for travel and/or speaker honoraria from Merck Serono, Biogen, BMS, Novartis, Roche, Genzyme, and Teva Pharmaceutical Industries Ltd. His institution received grants supporting research for my department from Merck Serono, Biogen, Genzyme, and Novartis. Mickael Zedet reported receiving personal fees from Novartis and Alexion, meeting invitations from Merck, Roche, Sanofi, and Sandoz, and travel expenses from Merk, Sandoz, and Novartis outside the submitted work.
ACKNOWLEDGMENTS
The authors thank Mrs. Senia Belkorche for her help in gathering data, the Observatoire Français de la Sclérose en Plaques (OFSEP, http://www.ofsep.org/fr/ ), which is supported by a grant provided by the French government and administered by the Agence Nationale de la Recherche , within the framework of the “Investments for the Future” program (reference ANR‐10‐COHO‐ 002) and the Eugène Devic EDMUS Foundation against Multiple Sclerosis.
Cohen M, Rollot F, Debouverie M, et al. Secondary progression activity monitoring in MS despite an early highly active treatment the SPAM study. Eur J Neurol. 2025;32:e16583. doi: 10.1111/ene.16583
DATA AVAILABILITY STATEMENT
The individual data from this study can be obtained upon request and after validation from the OFSEP scientific committee.
REFERENCES
Associated Data
Data Availability Statement
The individual data from this study can be obtained upon request and after validation from the OFSEP scientific committee.