Elicit: B-cell Biomarkers and Ocrelizumab Response

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B-cell Biomarkers and Ocrelizumab Response

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May 5, 2026

Which biomarkers of B-cell depletion correlate with clinical response to ocrelizumab?

CD19+ B-cell counts, plasmablast levels, baseline regulatory cell populations (CD49d+ T-cells and B-1a cells), and CD8+ T-cell depletion correlate with clinical response to ocrelizumab, with the relative importance of each biomarker varying by MS subtype and baseline inflammatory status.

Abstract

Multiple biomarkers of B-cell depletion correlate with clinical response to ocrelizumab, though their predictive value varies by clinical context. Total CD19+ B-cell depletion showed consistent associations with outcomes in RRMS, with higher ocrelizumab exposure producing lower B-cell counts and reduced disability progression (HR 0.64, p=0.0135). Baseline CD19+ counts predicted repopulation kinetics, with counts ≥12-14% identifying patients at risk for fast repopulation and higher MRI activity (17.39% vs. 2.53%, p=0.008). Plasmablast levels emerged as particularly informative: responders at 24 months had 3-fold lower plasmablasts at 6 months compared to non-responders (7.69% vs. 22.66%, p=0.043), and plasmablast populations correlated positively with 12-month EDSS scores (R=0.564, p=0.004). However, in PPMS, baseline inflammatory status determined which biomarkers mattered—B-cell repopulation and serum neurofilament levels predicted outcomes in Gd+ patients, while serum IgA levels and T-cell remodeling were more relevant in Gd- patients. Elevated baseline regulatory populations (CD49d+ T-cells, B-1a cells) predicted achievement of NEDA-3 status, while CD8+ T-cell modulation correlated with disability outcomes (OR=1.01, p=0.02). Treatment-naive patients demonstrated stronger biomarker-outcome correlations than previously treated patients (HR=2.53 for radiological activity with prior treatment, p=0.039), suggesting prior therapies modify B-cell compartment dynamics and diminish predictive accuracy of standard depletion metrics.

Methods

We analyzed 10 sources from an initial pool of 200, using 8 screening criteria. Each paper was reviewed for 5 key aspects that mattered most to the research question. More on methods

Records from Elicit search

n = 200

Papers screened using: Ocrelizumab Treatment, B-cell Depletion Biomarkers, Clinical Response Outcomes, Quantitative Correlation Analysis, Follow-up Biomarker Measurements, Adequate Sample Size, Full-text Publication, Ocrelizumab-specific Data

n = 200

Papers screened out

n = 190

Papers included for extraction

n = 10

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Paper search

We performed a semantic search across over 138 million academic papers from the Elicit search engine, which includes all of Semantic Scholar and OpenAlex.

We ran this query: “Which biomarkers of B-cell depletion correlate with clinical response to ocrelizumab?”

The search returned 200 total results from Elicit.

We retrieved 200 papers most relevant to the query for screening.

Screening

We screened in sources based on their abstracts that met these criteria:

We considered all screening questions together and made a holistic judgement about whether to screen in each paper.

Data extraction

We asked a large language model to extract each data column below from each paper. We gave the model the extraction instructions shown below for each column.

Extract all biomarkers of B-cell depletion that were measured, including:

Extract all measures used to assess clinical response to ocrelizumab, including:

Extract all reported correlations, associations, or relationships between B-cell depletion biomarkers and clinical response outcomes, including:

Extract patient characteristics that may influence biomarker-clinical response relationships, including:

Extract the main conclusions about which biomarkers of B-cell depletion correlate with clinical response to ocrelizumab, including:

Results

Characteristics of Included Studies

All 10 studies evaluated biomarkers of B-cell depletion in patients treated with ocrelizumab, though they varied in MS subtype, sample size, and follow-up duration.

Study

Full text retrieved?

MS Subtype

Sample Size

Follow-up Duration

Previous Treatment

Baseline EDSS (median/mean)

S. Hauser et al., 2023

Yes

RRMS and PPMS

Not specified

96 weeks (RRMS), variable (PPMS)

Randomized to ocrelizumab or comparator

Not specified

Ece Akbayır et al., 2025

Yes

RRMS

31

12 months

Previously treated, resistant to first-line agents

Not specified

M. Boziki et al., 2022

Yes

Active PPMS

22

24 months

Treatment-naive for immunosuppressants

4.91 (mean)

J. I. Fernández-Velasco et al., 2021

Yes

PPMS

53

6 months

Not specified

6 (median)

Alice Willison et al., 2025

Yes

RRMS

34 OCR, 25 OFA, 20 treatment-naive

12 months

Median 1 previous DMT (OCR and OFA groups); 25 treatment-naive

2.00 (median)

M. Cellerino et al., 2021

Yes

RRMS (n=93), PPMS (n=43), SPMS (n=17)

153

1.9 years (median)

76.95% previously treated

Lower baseline EDSS associated with better outcomes

Hany Mohammed Amin Aref et al., 2024

No

RRMS

30

12 months

Most had two previous DMTs; 13.3% treatment-naive

4.5 (median)

G. Abbadessa et al., 2021

Yes

RRMS (n=127), SPMS (n=43), PPMS (n=48)

218 (155 at 12 months)

At least 6 months; 155 with 12-month follow-up

76.95% previously treated; 23.04% treatment-naive

Not specified

J. I. Fernández-Velasco et al., 2022

Yes

PPMS

69

12 months

Not specified

5.5 (median)

Nicola Capasso et al., 2022

Yes

RRMS, SPMS, PPMS

78

36.5 months (mean)

Previous DMTs collected at baseline

Not specified

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The included studies represented diverse MS populations, with sample sizes ranging from 22 to 218 patients. Most studies (8 of 10) had full-text availability. Follow-up durations ranged from 6 months to 36.5 months. The majority of patients across studies had prior treatment exposure, though several studies included treatment-naive cohorts. Baseline disability varied substantially, with median/mean EDSS scores ranging from 2.00 to 6.0, reflecting heterogeneity in disease severity.

B-Cell Depletion Biomarkers Measured

Studies employed diverse approaches to quantify B-cell depletion, though CD19+ B cells emerged as the most commonly measured biomarker. S. Hauser et al. measured CD19+ B cells in cells/μL and categorized patients by median B-cell levels (0, 1-5, and >5 cells/μL). Hany Mohammed Amin Aref et al. reported baseline CD19 B cell counts of 65.98 ± 79.04 cells/μl, which depleted to 3.59 ± 2.94 cells/μl at 1 month, 25.6 ± 43.98 cells/μl at 6 months, and 11.11 ± 19.53 cells/μl at 12 months. G. Abbadessa et al. measured CD19 as a percentage, reporting baseline values of 12.94% that decreased to 0.45% after 12 months.

Several studies examined specific B-cell subsets beyond total CD19+ counts. Ece Akbayır et al. quantified plasma cells (CD19+ CD38+ CD138+), which were significantly suppressed at 12 months, along with naive B-cells (CD19+ CD27-IgD+) and switched memory B-cells (CD19+ CD27+ IgD-). M. Boziki et al. used 9-color multiparametric flow cytometry to assess plasmablasts, transitional B-cells, marginal-zone-like B-cells, class-switched memory B-cells, non-switched CD27+ memory B-cells, and naive B-cells, with particular focus on plasmablast percentages of CD19+ cells. J. I. Fernández-Velasco et al. reported drastic reduction in naive and memory B cells, along with significant increases in the proportions of plasmablasts and transitional B cells relative to total CD19+ B cells.

Alice Willison et al. documented significant reductions in CD20+ T and B cells, various B-cell subsets (naive B cells, regulatory B cells, marginal zone B cells, memory B cells, transitional B cells), and noted an expansion of CD5+CD19+CD20− B cells at months 1 and 12. Nicola Capasso et al. measured total lymphocyte counts and CD19+ and CD20+ subpopulations, reporting reductions that remained stable after the first infusion.

Two studies categorized patients based on repopulation kinetics. G. Abbadessa et al. identified fast repopulation (FR) and slow repopulation (SR) groups, with FR patients showing higher baseline CD19 cell counts (12% for 6-month cut-off, 14% for 12-month cut-off). S. Hauser et al. noted complete depletion with slow repopulation, with median time to B-cell repletion of 72 weeks.

Clinical Response Measures

Studies used heterogeneous outcome measures to assess clinical response to ocrelizumab. Disability progression was measured using confirmed disability progression (CDP) at 24 weeks, confirmed disability accumulation (CDA), confirmed disability worsening, and EDSS progression. EDSS scores were reported at various timepoints across studies.

Relapse-related outcomes included annualized relapse rate (ARR), time to first relapse, and number of attacks. ARR was significantly reduced from 20 to 0 after 12 months in the Aref et al. study and reached very low levels (0.13-0.18) across exposure quartiles in the Hauser et al. analysis.

MRI outcomes varied across studies. S. Hauser et al. assessed new/enlarging T2 lesions, T1 gadolinium-enhancing lesions, and brain volume changes. M. Boziki et al. measured new/enlarging T2 lesions and brain volume changes, with significant effects on gray matter cerebellar volume (F=4.342, p=0.23) and normalized gray matter cerebellar volume (F=4.279, p=0.024). Several studies evaluated the presence or absence of Gd-enhancing lesions.

Composite measures were employed in multiple studies. NEDA-3 (no evidence of disease activity) was defined as absence of relapses, confirmed disability worsening, and MRI activity. Ece Akbayır et al. achieved NEDA-3 in 19 of 31 patients (61.3%). M. Boziki et al. defined optimal response as patients free of relapses, CDA, and new/enlarging T2 lesions, achieved by 63.6% at 12 months and 59.1% at 24 months. Hany Mohammed Amin Aref et al. used the Multiple Sclerosis Functional Composite score, which showed significant improvement across three timepoints.

Biomarker-Clinical Response Correlations

Total B-Cell and CD19+ Depletion

S. Hauser et al. demonstrated a dose-response relationship between ocrelizumab exposure, B-cell depletion, and clinical outcomes. Higher ocrelizumab exposure led to lower blood B-cell counts, and higher median B-cell levels were associated with greater rates of disability progression. The hazard ratio for disability progression was 0.64 (95% CI: 0.45-0.92; p=0.0135) favoring higher ocrelizumab exposure. Patients with more complete B-cell depletion showed greater reduction in risk of disability progression.

Hany Mohammed Amin Aref et al. found a statistically significant correlation between CD19 B cell counts and EDSS scores, with sustained CD19 B cell depletion associated with marked clinical and radiological improvement. However, no significant correlation was found with the Multiple Sclerosis Functional Composite score or MRI disease activity.

G. Abbadessa et al. identified baseline CD19 cell count as a predictor of repopulation kinetics and clinical outcomes. Higher baseline CD19 counts were associated with fast repopulation rate (FR). FR patients had significantly higher active MRI scans at 12 months compared to slow repopulation (SR) patients (17.39% vs. 2.53%; p=0.008). ROC curve analysis established cut-offs of 12% CD19 cells at baseline for predicting fast repopulation at 6 months (AUC=0.62) and 14% for 12 months (AUC=0.71).

B-Cell Subset Correlations

Plasmablasts emerged as a significant predictor of treatment response in multiple studies. M. Boziki et al. found that responders at 24 months had significantly reduced peripheral blood plasmablasts (7.69 ± 4.4% of CD19+ cells) compared to non-responders (22.66 ± 7.19%) at the 6-month timepoint (p=0.043). This was the first study to link reduced plasmablast depletion to suboptimal response in active PPMS.

Ece Akbayır et al. demonstrated that month 12 EDSS scores correlated positively with plasmablast populations (R=0.564, p=0.004). Additionally, reduced post-treatment populations of switched memory B-cells were negatively correlated with treatment efficacy, suggesting that failure to suppress these populations indicates reduced treatment response.

Memory B-cell dynamics showed complex patterns. While Ece Akbayır et al. found reduced switched memory B-cells associated with better outcomes, J. I. Fernández-Velasco et al. reported significant reductions in both naive and memory B cells that correlated with decreased serum neurofilament light chain (sNfL) levels (p<0.0001 for B-cell reduction; p=0.008 for sNfL reduction).

J. I. Fernández-Velasco et al. (2022) observed that low repopulation rate of inflammatory B cells and reduced sNfL levels were associated with NEDA status in patients with gadolinium-enhancing lesions (Gd+). In Gd- patients, low B-cell numbers and sNfL levels were observed, but increases in serum IgA levels and IgA/IgM ratio were more significant for NEDA status.

Regulatory Cell Populations

Elevated baseline populations of regulatory cells predicted better outcomes. Ece Akbayır et al. found that baseline regulatory CD49d+ T-cells and B-1a cells were positively correlated with achieving NEDA-3 status. Alice Willison et al. reported that CD5 expression on B cells was negatively correlated with EDSS at baseline (r=-0.496, p=0.001) and positively correlated with time since last relapse (r=0.456, p=0.004).

Naive T-cell populations also showed protective associations. Ece Akbayır et al. found increased post-treatment populations of naive T-cells were positively correlated with lower EDSS scores at month 6 (R=-0.515 and R=-0.602, p=0.003) and higher rates of NEDA-3 status.

T-Cell and Exhaustion Markers

M. Cellerino et al. identified CD8+ cells as a potential biomarker, with the decrease in CD8+ cells being less pronounced in patients with inflammatory activity (p=0.022). CD8+ cell count was independently associated with early inflammatory activity (OR 1.005, 95% CI 1.001-1.009, p=0.019).

Nicola Capasso et al. found that higher probability of EDSS progression was associated with reduced modulation (i.e., higher levels) of CD8 lymphocytes (OR=1.01, 95% CI=1.00-1.05, p=0.02), suggesting that progressive reduction of CD8 cytotoxic T-lymphocytes correlates with clinical stability.

Alice Willison et al. documented extensive correlations with exhaustion markers. TIGIT expression on CD8+ T cells was negatively correlated with EDSS at baseline (r=-0.35, p=0.029) and positively correlated with time since disease manifestation (r=0.422, p=0.007). TIM-3 expression on CD4+ T cells showed negative correlation with baseline EDSS (r=-0.393, p=0.013). PD-1 expression on B cells was positively correlated with EDSS at month 1 (r=0.37, p=0.0341), while CTLA-4 expression on NKT cells was negatively correlated with EDSS at month 1 in OCR-treated patients (r=-0.516, p=0.0487).

Double-negative T cells (KLRG1-HLADR+ DN T cells) showed a positive correlation with the number of relapses prior to baseline (r=0.322, p=0.01) and negative correlation with EDSS at month 12 (r=-0.573, p=0.0161).

Patient-Level Predictors

Lower baseline EDSS was independently associated with reduced risk of disability worsening (HR=1.45, 95% CI 1.05-2.00, p=0.024). Previous treatment exposure was independently associated with increased probability of radiological activity (HR=2.53, 95% CI 1.05-6.10, p=0.039), suggesting treatment-naive patients may respond better to ocrelizumab.

Synthesis

The studies reveal complex, context-dependent relationships between B-cell depletion biomarkers and clinical response to ocrelizumab. Rather than a single biomarker universally predicting outcomes, different markers appear relevant in different clinical contexts.

MS Subtype as a Context Modifier

The relevance of specific biomarkers varies by MS subtype. In RRMS populations, total B-cell depletion metrics (CD19+ counts, repopulation kinetics) showed strong associations with clinical outcomes. The Hauser et al. post-hoc analysis of the OPERA trials demonstrated clear dose-response relationships in RRMS, with hazard ratios for disability progression ranging from 0.70 in the lowest exposure quartile to 0.34 in the highest quartile versus interferon β-1a.

In PPMS populations, the pattern differed substantially. While Hauser et al. observed similar trends (hazard ratios ranging from 0.88 to 0.55 across quartiles), the PPMS-specific studies revealed that baseline inflammatory status fundamentally altered which biomarkers mattered. Fernández-Velasco et al. (2022) demonstrated that in Gd+ PPMS patients, B-cell repopulation rate and sNfL levels predicted NEDA status, whereas in Gd- patients, the same B-cell metrics showed no predictive value, with serum IgA levels and T-cell/innate immune remodeling instead correlating with outcomes. This suggests that in non-inflammatory PPMS, B-cell depletion enables immune modulation through indirect mechanisms rather than directly suppressing inflammatory B cells.

The Plasmablast Paradox

Multiple studies identified plasmablasts as paradoxically important despite representing a small fraction of circulating B cells. Boziki et al. found that responders had 3-fold lower plasmablasts (7.69% vs. 22.66% of CD19+ cells, p=0.043) at 6 months, while Akbayır et al. showed plasmablast populations correlated positively with 12-month EDSS scores (R=0.564, p=0.004). Fernández-Velasco et al. (2021) noted that plasmablast proportions increased significantly after ocrelizumab, seemingly contradicting their role as a negative prognostic marker.

This apparent contradiction resolves when considering that ocrelizumab depletes CD20+ B cells but spares CD20-negative plasmablasts and plasma cells. The increase in plasmablast proportion (relative to depleted total B cells) does not indicate absolute expansion. Studies measuring absolute plasmablast depletion efficiency—rather than proportional changes—consistently found that incomplete plasmablast suppression predicts worse outcomes. This suggests residual plasmablasts may sustain pathogenic antibody production or represent reservoirs for rapid B-cell reconstitution.

Baseline Biomarkers Versus Dynamic Markers

Studies diverged on whether baseline or post-treatment biomarker levels better predicted outcomes, likely reflecting different mechanistic questions. Baseline CD19+ counts predicted repopulation kinetics: Abbadessa et al. established that baseline counts ≥12-14% identified patients who would experience fast repopulation and higher MRI activity. This suggests baseline B-cell burden determines the “depth” of achievable depletion with standard dosing.

Conversely, post-treatment dynamics—particularly at 6 months—predicted clinical trajectories in multiple studies. Boziki et al. found 6-month plasmablast levels distinguished responders from non-responders at 24 months, while Akbayır et al. showed that 6-month switched memory B-cell levels and naive T-cell populations correlated with NEDA-3 status. This 6-month timepoint may represent a critical window when the balance between depletion efficacy and early reconstitution becomes apparent, before full disease reactivation occurs.

The T-Cell Connection: Indirect Effects of B-Cell Depletion

Several studies identified T-cell populations as biomarkers despite ocrelizumab targeting CD20. Cellerino et al. found CD8+ cell counts independently associated with inflammatory activity (OR 1.005, p=0.019), while Capasso et al. showed reduced CD8+ modulation predicted EDSS progression (OR=1.01, p=0.02). These findings reflect that ocrelizumab depletes CD20+ T cells alongside B cells, with Cellerino et al. explicitly linking CD8+ depletion to reduced CD20+ T cells.

Willison et al. provided the most comprehensive T-cell profiling, demonstrating that exhaustion markers (TIGIT, TIM-3, PD-1, CTLA-4) on T, B, NK, and NKT cells increased with ocrelizumab and correlated with clinical parameters. TIGIT expression showed particularly consistent protective correlations across cell types (negative correlation with EDSS, positive correlation with time since manifestation). These findings suggest ocrelizumab induces a broader immune remodeling toward an exhausted/regulatory phenotype, potentially explaining efficacy beyond simple B-cell depletion.

Regulatory T-cell expansion provided mechanistic insight: Akbayır et al. found elevated baseline regulatory CD49d+ T-cells and B-1a cells predicted NEDA-3 status, while Willison et al. documented CD5+CD19+CD20− B cell expansion. This suggests successful treatment may depend on concurrent expansion of regulatory populations that suppress residual effector cells.

Treatment History as a Confounding Factor

Previous treatment exposure consistently modified biomarker-response relationships. Cellerino et al. found prior DMT exposure independently increased radiological activity risk (HR=2.53, p=0.039), while treatment-naive patients had higher NEDA-3 probabilities. Abbadessa et al.’s cohort was 76.95% previously treated, potentially explaining why baseline CD19 counts varied so widely (sufficient to create meaningful quartiles for analysis).

This likely reflects that prior treatments alter the B-cell compartment’s composition and repopulation capacity. Patients who failed previous therapies may have more aggressive disease biology, enrichment for treatment-resistant B-cell clones, or altered B-cell homeostatic mechanisms. The stronger biomarker-outcome correlations in treatment-naive cohorts suggest that without prior perturbations, B-cell depletion metrics more directly reflect disease activity.

Dose-Response and Threshold Effects

The Hauser et al. exposure-response analysis revealed a critical asymmetry: while ARR and MRI lesions reached near-zero levels across all exposure quartiles (suggesting a ceiling effect), disability progression showed continuous exposure-dependent improvement. This suggests different disease processes have different B-cell dependency thresholds. Inflammatory relapses and focal lesions may require only moderate B-cell depletion (achievable at lower exposures), while disability progression—potentially driven by compartmentalized inflammation or chronic B-cell activity in CNS tissues—benefits from maximal depletion.

Abbadessa et al.’s ROC analysis established practical cut-offs (12% and 14% baseline CD19), but the modest AUCs (0.62 and 0.71) indicate substantial overlap between responders and non-responders. This suggests baseline counts provide risk stratification rather than deterministic prediction, and that other factors (genetic, compartmentalized immunity) substantially influence outcomes.

Reconciling Heterogeneity: Toward an Integrated Model

The apparent heterogeneity in biomarker findings reflects that B-cell depletion operates through multiple mechanisms that vary by clinical context:

  1. In inflammatory RRMS/active PPMS: Direct suppression of pathogenic B cells (measured by CD19+ counts, plasmablast depletion) correlates with reduced relapses and MRI activity.

  2. In non-inflammatory PPMS: B-cell depletion enables immune remodeling (measured by regulatory cell expansion, IgA changes, T-cell modulation) that indirectly affects progression.

  3. Across all subtypes: Completeness of depletion (measured by repopulation kinetics, residual plasmablasts) predicts durability of response, while baseline regulatory populations (CD49d+ T-cells, B-1a cells) predict capacity for beneficial immune remodeling.

  4. In previously treated patients: Altered B-cell compartments and potentially resistant clones diminish predictive value of standard depletion metrics.

Rather than seeking a single “best” biomarker, these findings suggest clinical response depends on achieving adequate depletion and favorable immune reconstitution. Baseline metrics (CD19 counts, regulatory cells) predict depletion depth and reconstitution quality, while early post-treatment measures (6-month plasmablasts, memory B-cells, T-cell profiles) predict the realized treatment response before clinical outcomes fully manifest.

References

Ece Akbayır, Tugce Kizilay, Ruziye Erol, Duygu OZKAN‐YASARGUN, E. Tuzun, and 2 more\ (2025).B‐Cell and T‐Cell Populations in Peripheral Blood Linked to Ocrelizumab Treatment Efficacy in Multiple Sclerosis. In Vivo

M. Boziki, C. Bakirtzis, Styliani-Aggeliki Sintila, E. Kesidou, Evdoxia Gounari, and 11 more\ (2022).Ocrelizumab in Patients with Active Primary Progressive Multiple Sclerosis: Clinical Outcomes and Immune Markers of Treatment Response. Cells

J. I. Fernández-Velasco, J. Kuhle, E. Monreal, V. Meca-Lallana, J. Meca-Lallana, and 20 more\ (2021).Effect of Ocrelizumab in Blood Leukocytes of Patients With Primary Progressive MS. Neurology: Neuroimmunology & Neuroinflammation

Alice Willison, Ramona Hagler, M. Weise, S. Elben, Niklas Huntemann, and 16 more\ (2025).Effects of Anti-CD20 Antibody Therapy on Immune Cell Dynamics in Relapsing-Remitting Multiple Sclerosis. Cells

M. Cellerino, G. Boffa, C. Lapucci, F. Tazza, E. Sbragia, and 11 more\ (2021).Predictors of Ocrelizumab Effectiveness in Patients with Multiple Sclerosis. Neurotherapeutics

Hany Mohammed Amin Aref, Azza Abd El-Nasser Abdelaziz, Abeer Al-Sayed Ali Shehab, D. Zamzam, Alaa Mohamed Abou Steit, and 1 more\ (2024).Follow Up of Total B Cells (CD 19) Count after B Cell Depleting Therapy in Relapse Remitting Multiple Sclerosis Disorder in Egyptian Patients. The Quarterly journal of medicine

G. Abbadessa, G. Miele, P. Cavalla, P. Valentino, G. Marfia, and 10 more\ (2021).CD19 Cell Count at Baseline Predicts B Cell Repopulation at 6 and 12 Months in Multiple Sclerosis Patients Treated with Ocrelizumab. International Journal of Environmental Research and Public Health

J. I. Fernández-Velasco, E. Monreal, J. Kuhle, V. Meca-Lallana, J. Meca-Lallana, and 26 more\ (2022).Baseline Inflammatory Status Reveals Dichotomic Immune Mechanisms Involved In Primary-Progressive Multiple Sclerosis Pathology. Frontiers in Immunology

Nicola Capasso, R. Palladino, Vincenza Cerbone, A. Spiezia, B. Covelli, and 8 more\ (2022).Ocrelizumab effect on humoral and cellular immunity in multiple sclerosis and its clinical correlates: a 3-year observational study. Journal of Neurology

S. Hauser, A. Bar-Or, Martin S. Weber, H. Kletzl, A. Günther, and 8 more\ (2023).Association of Higher Ocrelizumab Exposure With Reduced Disability Progression in Multiple Sclerosis. Neurology: Neuroimmunology & Neuroinflammation

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Association of Higher Ocrelizumab Exposure With Reduced Disability Progression in Multiple Sclerosis

S. Hauser, A. Bar-Or, Martin S. Weber, H. Kletzl, A. Günther, M. Manfrini, F. Model, F. Mercier, Claire Petry, Qing Wing, H. Koendgen, Terence Smith, L. Kappos

Neurology: Neuroimmunology & Neuroinflammation·

2023·

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B-Cell Depletion Biomarkers

- Specific cell type/markers: CD19+ B cells - Measurement units: cells/μL - Baseline values and follow-up timepoints: Not explicitly detailed - Depletion patterns: Complete depletion with slow repopulation - Categorizations: Grouped by median B-cell levels (0, 1-5, and >5 cells/μL)

Clinical Response Measures

- Relapse-related outcomes: Annualized relapse rate (ARR) - Disability measures: Confirmed disability progression (CDP) at 24 weeks, composite measure of disability progression (cCDP) - MRI outcomes: New/enlarging T2 lesions, T1 gadolinium-enhancing lesions, brain volume changes - Timepoints: Week 96 for ARR, week 24 for CDP

Biomarker-Response Correlations

- Correlation between ocrelizumab serum concentration and B-cell depletion: Higher exposure leads to lower blood B-cell counts. - Trend: Higher median B-cell levels associated with greater rates of disability progression. - Association: More B-cell depletion associated with greater reduction in risk of disability progression. - Hazard Ratio (HR): Lower HR for disability progression with higher ocrelizumab exposure (HR 0.64 [95% CI: 0.45-0.92; p = 0.0135]). - Predictive relationship: Higher ocrelizumab exposure and greater B-cell depletion associated with improved clinical outcomes.

Patient Characteristics

- MS subtype: Relapsing multiple sclerosis (RMS), Primary progressive multiple sclerosis (PPMS) - Baseline demographic characteristics: Higher proportions of males, higher weight/BMI in lower exposure quartiles - Baseline disease activity: Presence of T1 gadolinium-enhancing lesions lower in lower exposure quartiles - Previous treatment history: Randomized to ocrelizumab or comparator (IFN β-1a for RMS, placebo for PPMS) - Sample size and follow-up duration: Treatment period of 96 weeks for RMS, variable for PPMS

Key Findings

- Primary findings: Higher ocrelizumab exposure correlates with lower rates of confirmed disability progression (CDP) and more complete B-cell depletion. - Clinical implications: Higher exposure may improve control of disability progression by reducing disease activity and attenuating B-cell-related pathologies. - Recommendations: Higher doses of ocrelizumab could improve efficacy without increasing serious adverse events. - Limitations: The study is post hoc, and the analysis is subject to limitations of sample and effect sizes. - Future research directions: Further exploration of the benefits of higher doses in controlled prospective clinical studies is recommended.

Background and Objectives Ocrelizumab improved clinical and MRI measures of disease activity and progression in three phase 3 multiple sclerosis (MS) studies. Post hoc analyses demonstrated a correlation between the ocrelizumab serum concentration and the degree of blood B-cell depletion, and body weight was identified as the most influential covariate on ocrelizumab pharmacokinetics. The magnitude of ocrelizumab treatment benefit on disability progression was greater in lighter vs heavier patients. These observations suggest that higher ocrelizumab serum levels provide more complete B-cell depletion and a greater delay in disability progression. The current post hoc analyses assessed population exposure–efficacy/safety relationships of ocrelizumab in patients with relapsing and primary progressive MS. Methods Patients in OPERA I/II and ORATORIO were grouped in exposure quartiles based on their observed individual serum ocrelizumab level over the treatment period. Exposure–response relationships were analyzed for clinical efficacy (24-week confirmed disability progression (CDP), annualized relapse rate [ARR], and MRI outcomes) and adverse events. Results Ocrelizumab reduced new MRI lesion counts to nearly undetectable levels in patients with relapsing or primary progressive MS across all exposure subgroups, and reduced ARR in patients with relapsing MS to very low levels (0.13–0.18). A consistent trend of higher ocrelizumab exposure leading to lower rates of CDP was seen (0%–25% [lowest] to 75%–100% [highest] quartile hazard ratios and 95% confidence intervals; relapsing MS: 0.70 [0.41–1.19], 0.85 [0.52–1.39], 0.47 [0.25–0.87], and 0.34 [0.17–0.70] vs interferon β-1a; primary progressive MS: 0.88 [0.59–1.30], 0.86 [0.60–1.25], 0.77 [0.52–1.14], and 0.55 [0.36–0.83] vs placebo). Infusion-related reactions, serious adverse events, and serious infections were similar across exposure subgroups. Discussion The almost complete reduction of ARR and MRI activity already evident in the lowest quartile, and across all ocrelizumab-exposure groups, suggests a ceiling effect. A consistent trend of higher ocrelizumab exposure leading to greater reduction in risk of CDP was observed, particularly in the relapsing MS trials, and was not associated with a higher rate of adverse events. Higher ocrelizumab exposure may provide improved control of disability progression by reducing disease activity below that detectable by ARR and MRI, and/or by attenuating other B-cell–related pathologies responsible for tissue damage. Classification of Evidence This analysis provides Class III evidence that higher ocrelizumab serum levels are related to greater reduction in risk of disability progression in patients with multiple sclerosis. The study is rated Class III because of the initial treatment randomization disclosure that occurred after inclusion in the open-label extension. Trial Registration Information ClinicalTrials.gov Identifier: NCT01247324 (OPERA I), NCT01412333 (OPERA II), and NCT01194570 (ORATORIO).

Methods

Patients in OPERA I/II and ORATORIO were grouped in exposure quartiles based on their observed individual serum ocrelizumab level over the treatment period. Exposure-response relationships were analyzed for clinical efficacy (24-week confirmed disability progression (CDP), annualized relapse rate [ARR], and MRI outcomes) and adverse events.

Results

Ocrelizumab reduced new MRI lesion counts to nearly undetectable levels in patients with relapsing or primary progressive MS across all exposure subgroups, and reduced ARR in patients with relapsing MS to very low levels (0.13-0.18). A consistent trend of higher ocrelizumab exposure leading to lower rates of CDP was seen (0%-25% [lowest] to 75%-100% [highest] quartile hazard ratios and 95% confidence intervals; relapsing MS: 0.70 [0.41-1.19], 0.85 [0.52-1.39], 0.47 [0.25-0.87], and 0.34 [0.17-0.70] vs interferon β-1a; primary progressive MS: 0.88 [0.59-1.30], 0.86 [0.60-1.25], 0.77 [0.52-1.14], and 0.55 [0.36-0.83] vs placebo). Infusion-related reactions, serious adverse events, and serious infections were similar across exposure subgroups.

Discussion

The almost complete reduction of ARR and MRI activity already evident in the lowest quartile, and across all ocrelizumab-exposure groups, suggests a ceiling effect. A consistent trend of higher ocrelizumab exposure leading to greater reduction in risk of CDP was observed, particularly in the relapsing MS trials, and was not associated with a higher rate of adverse events. Higher ocrelizumab exposure may provide improved control of disability progression by reducing disease activity below that detectable by ARR and MRI, and/or by attenuating other B-cell-related pathologies responsible for tissue damage.

Class of Evidence

Criteria for rating therapeutic and diagnostic studies NPub.org/coe

Classification of Evidence

This analysis provides Class III evidence that higher ocrelizumab serum levels are related to greater reduction in risk of disability progression in patients with multiple sclerosis. The study is rated Class III because of the initial treatment randomization disclosure that occurred after inclusion in the open-label extension.

Trial Registration Information ClinicalTrials.gov Identifier: NCT01247324 (OPERA I), NCT01412333 (OPERA II), and NCT01194570 (ORATORIO).

Ocrelizumab, at an IV dose of 600 mg every 6 months, was the first CD20 + B-cell-selective humanized monoclonal antibody 1 approved for the treatment of patients with relapsing multiple sclerosis (RMS) or primary progressive multiple sclerosis (PPMS).

Ocrelizumab had significant benefit on 12-and 24-week confirmed disability progression (12 W-CDP and 24 W-CDP), annualized relapse rate (ARR), and MRI measures vs comparator in pivotal phase 3 studies in patients with RMS 2 or PPMS, 3 with sustained efficacy in the respective open-label extension (OLE) periods. 4,5 Further analysis of data from these studies 6 and others 7,8 has demonstrated that most disability progression in patients with RMS receiving disease-modifying therapies (DMTs) occurs independent of relapse activity, and is attributable to an underlying and continuous progressive disease course. Although ocrelizumab demonstrated substantial reductions of disability progression in patients with both RMS and PPMS, the need for providing a more pronounced effect on disability progression, or even stopping disability progression altogether, remains the greatest challenge to the field.

In pharmacokinetic and pharmacodynamic analyses of the OPERA I, OPERA II, and ORATORIO studies, a correlation between the individual ocrelizumab serum concentration over the treatment period for each patient and the level of B-cell depletion in blood was observed, 9 where higher ocrelizumab exposure led to lower blood B-cell counts in patients with RMS and PPMS. The population pharmacokinetic analysis identified body weight as the most influential covariate on ocrelizumab serum levels. In the prespecified subgroup analyses of ocrelizumab efficacy in the pooled OPERA trials, body mass index (BMI) showed a significant treatment-bysubgroup interaction for both 12 W-and 24 W-CDP endpoints, indicating that the magnitude of ocrelizumab treatment benefit on disability progression was greater in lighter vs heavier patients (BMI ≤25 kg/m2 vs >25 kg/m 2 ). 10 A plausible explanation for this observation could be that higher ocrelizumab exposure in lighter patients leads to more complete B-cell depletion and to a more pronounced delay in disability progression. In this study, we investigated the relationship between higher ocrelizumab exposure and clinical, imaging, and safety outcomes, with a special focus on disability progression.

Standard Protocol Approvals, Registrations, and Patient Consents

The relevant institutional review boards/ethics committees approved the trial protocols (NCT01247324, NCT01412333, and NCT01194570). All patients provided written informed consent.

Trial Design and Patients

3][4][5] In the phase 3 studies, patients received the approved dose of ocrelizumab (600 mg administered IV preceded by 100 mg methylprednisolone [or equivalent] IV every 6 months) or comparator. Patients with RMS were randomized 1:1 to ocrelizumab or subcutaneous interferon (IFN) β-1a 44 μg 3 times weekly for 96 weeks, whereas those with PPMS were randomized 2:1 to either ocrelizumab or placebo every 24 weeks until the last enrolled patient completed at least 120 weeks of study treatment and the planned total number of CDP events had been reached (median 7 doses).

Measures of Exposure

Ocrelizumab serum concentrations were measured with a validated ELISA with a lower limit of quantitation of 250 ng/mL, as described previously. 9 Briefly, blood samples for pharmacokinetic assessments were drawn in OPERA: predose at weeks 1, 24, 48, and 72; 30 minutes postinfusion at week 72; and on days 84 and 96; and in ORATORIO: preinfusion on days 1 and 15, and at weeks 24, 48, 72, and 96; 30 minutes postinfusion on days 1 and 15 and at week 72; and at weeks 12, 84, and 120. The serum concentration data were analyzed using the population pharmacokinetic method. Concentration vs time curves over the 6-monthly dosing intervals were modeled from the individual estimated pharmacokinetic parameters, and subsequently C mean , i.e., the average concentration over the treatment period, derived for each patient. Ocrelizumab exposure (C mean ) was defined as the average ocrelizumab serum concentration in an individual patient during their treatment with ocrelizumab. The exposure quartiles split all patients into 4 equal groups based on where an individual's exposure ranks in the range of ocrelizumab serum concentrations observed in the study patient population. For patients who received all planned doses, this corresponded to the average concentration over the entire treatment period of 96 weeks in patients with RMS in OPERA I and OPERA II, whereas treatment duration varied in patients with PPMS because of the event-driven design of the ORATORIO study (median [range] number of infusions: OPERA I/II, 4 [1-4]; ORATORIO, 7 [1-10]).

For investigation of the potential association between a patient's ocrelizumab serum level and clinical outcomes, ocrelizumab-treated patients were divided into subgroups based on the quartiles of the serum ocrelizumab exposure range. In patients with RMS, the ranges for ocrelizumab exposure Quartiles 1-4 were min-<15.4, ≥15.4-<18.7, ≥18.7-<22.2, and ≥22.2-max μg/mL, respectively. The corresponding ranges in patients with PPMS were min-<15.8, ≥15.8-<18.9, ≥18.9-<23.2, and ≥23.2-max μg/mL. 9 To estimate treatment effects between ocrelizumab and control within comparable patient groups, ocrelizumab and IFN β-1a-treated patients were divided into subgroups based on BMI as a strong predictor of ocrelizumab exposure.

Endpoints and Populations Analyzed

Analyses of endpoints in patients with RMS and PPMS are based on the pooled population of OPERA I and OPERA II, and ORATORIO, respectively. Unless otherwise stated, analyses of endpoints are based on the complete double-blind controlled treatment phases (96 weeks for OPERA I and OPERA II [pooled data], >120 weeks for ORATORIO). For B-cell-related endpoints, the OLE was included for the ocrelizumab-treated patients from the pooled population of OPERA I and OPERA II, and the extended-controlled period and OLE for the ORATORIO population. 4,5 posure-response analyses of ARR are presented only for patients with RMS because ARR was not specified as an endpoint in ORATORIO; the low number of protocol-defined relapses in ORATORIO also precluded any meaningful analysis. Analyses of 12 W-CDP, 24 W-CDP, MRI-based measures, and safety outcomes, including serious adverse events (SAEs), infusion-related reactions, and serious infections, are presented for both RMS and PPMS populations. MRI measures assessed were T1 gadolinium-enhancing lesions, new and/or enlarging T2 lesions, and percent change in whole brain volume from baseline; for brain volume change, MRI rebaselining at week 8 was also included to exclude MRI activity that occurs during the first 8 weeks of treatment before the potential treatment benefit of ocrelizumab is realized.

In addition to the exposure-response analyses of disability progression defined by the Expanded Disability Status Scale (EDSS) score (an increase from baseline of at least 1 point [or 0.5 points if the baseline EDSS score was >5.5]), analyses by baseline BMI quartile and blood B-cell depletion (3 groups based on the median blood CD19 + B-cell count over the treatment period of each patient, i.e., 0, 1-5, and >5 B cells/μL, or grouped by < and ≥ the median of the postbaseline median CD19 + B-cell count of each patient; blood CD19 + B-cell counts were assessed by flow cytometry), along with an exposure-response analysis of composite CDP (cCDP; first confirmed occurrence of an increase in the EDSS score and/or increase in Timed 25-Foot Walk [T25FW] or Nine-Hole Peg Test [9HPT] of ≥20%), were conducted.

Statistical Analyses

All patients with available ocrelizumab serum concentrations were included in the pharmacokinetic analysis. 9 Analyses of BMI subgroups were based on the intention-to-treat population and randomized treatment assignment. Time-toprogression analyses of exposure-outcome dependencies were based on a Cox regression model with a binary exposure main effect (low and high) based on a median exposure cut. Analyses of treatment effect within exposure quartiles were based on a Cox regression model, with treatment as the main effect, where treatment groups consisted of all control patients (IFN β-1a or placebo), and ocrelizumab-treated patients divided into 4 groups based on ocrelizumab exposure quartiles. For univariate subgroup analyses, ocrelizumabtreated patients were divided into 2 groups based on a median exposure cut; in addition to the treatment effect, the respective baseline covariate and its interaction with treatment were included in the Cox regression model. For the multivariate subgroup analyses, all baseline covariates and their interactions with treatment were fitted in 1 Cox regression model. For the exposure response analyses, the average serum concentration for a patient over their treatment period (C mean ) was treated as a time-invariant measure, because a patient's characteristics determining their pharmacokinetics are not expected to change over the observation period. For analyses of blood B-cell counts, the median CD19 + B-cell count over all postbaseline dosing visits was calculated for every patient (measured before the ocrelizumab infusion at weeks 24, 48, 72, 96, and for ORATORIO week 120) and ocrelizumab-treated patients were allocated to 3 groups of 0, 1-5, and >5 B cells/μL (based on the sensitivity of the assay, repeated B-cell counts of 0 and >5 cells/μL were considered to represent certainty on blood B-cell levels, with 1-5 cells/μL being between the thresholds of certainty). Patients with an initial disability progression during the controlled treatment period who discontinued treatment early without a subsequent EDSS assessment were censored for OPERA or imputed as having a CDP event for ORATORIO. Analyses of relapse and MRI lesion rates were based on Poisson regression models with follow-up time or number of MRI scans as an offset variable. Analyses of brain volume changes were performed using Mixed Model Repeated Measures regression. These analyses were post hoc; hence, the studies were likely underpowered to detect a statistically significant difference. However, consistent results for outcomes across exposure quartiles and B-cell levels lend support to the conclusions derived from the data; hence, the word "trend" is used whenever there is a numeric difference without reaching statistical significance, and a consistent pattern in outcomes is observed across the exposure quartiles and B-cell levels.

Data Availability

For eligible studies, qualified researchers may request access to individual patient-level clinical data through a data request platform. At the time of writing, this request platform is Vivli, vivli.org/ourmember/roche/. For up-to-date details of Roche's Global Policy on the Sharing of Clinical Information and how to request access to related clinical study documents, see go.roche.com/data_sharing.

Baseline Demographic and Disease Characteristics

In patients with RMS (Table 1 ), ocrelizumab exposuregrouped baseline demographic and disease characteristics were comparable for most covariates. Higher proportions of patients were male, had a higher weight/BMI, or were from the United States in lower exposure quartiles (Quartiles 1 and 2) vs higher quartiles (Quartiles 3 and 4). The presence of T1 gadoliniumenhancing lesions was lower in patients within the lower vs the higher exposure quartiles; however, no effect was noted between baseline enhancing lesions and progression outcomes. In patients with PPMS (Table 1 ), the pattern of exposuregrouped baseline demographic and disease characteristics was generally consistent with those observed in patients with RMS.

Annualized Relapse Rate Grouped by Ocrelizumab Exposure Quartile in Patients With RMS

In ocrelizumab-treated patients with RMS, adjusted ARRs through week 96 were low and comparable across exposure quartiles (Quartile 1, 0.14 [95% confidence interval (CI): 0.10-0.20]; Quartile 2, 0.18 [95% CI: 0.13-0.25]; Quartile 3, 0.13 [95% CI: 0.09-0.19]; Quartile 4, 0.17 [95% CI: 0.12-0.23]); the ARR in patients receiving IFN β-1a was 0.29 (95% CI: 0.25-0.34). The treatment effect of ocrelizumab relative to the IFN β-1a arm on ARR (rate ratios [RR]) in individual exposure quartiles is reported in Table 2 . Overall, no association between exposure and ARR was observed.

Disability Progression in Patients With RMS Confirmed Disability Progression Measured With the EDSS

An exposure dependency of time to onset of 24 W-CDP was seen within ocrelizumab-treated patients with RMS, when comparing high-exposure (combined Quartiles 3 and 4 [3/4]) with low-exposure (combined Quartiles 1 and 2 [1/2]) patients (hazard ratio [HR] 0.52 [95% CI: 0.30, 0.90; p = 0.0178]; Figure 1 ). Exposure dependency of 24 W-CDP was observed in the individual quartile exposure-grouped Kaplan-Meier analysis (Figure 2 ) and the associated HRs in ocrelizumab-treated patients compared with all IFN β-1a-treated patients (Figure 1 ). Point estimates of 24 W-CDP HRs vs IFN β-1a were lower in the higher exposure quartiles (Quartile 3, 0.47 [95% CI: 0.25-0.87; p = 0.02]; Quartile 4, 0.34 [95% CI: 0.17-0.70; p = 0.004]) compared with the lower exposure quartiles (Quartile 1, 0.70 [95% CI: 0.41-1.19; p = 0.19]; Quartile 2, 0.85 [95% CI: 0.52-1.39; p = 0.52]).

When comparing time to onset of 24 W-CDP between treatment arms (IFN β-1a vs ocrelizumab) within BMI quartiles, numerically, the greatest reductions in risk of disability progression were seen in the lower BMI quartiles (Figure 1 ). An important advantage of the BMI analysis is that it permits the control and treatment groups to be compared based on the same baseline patient characteristic as the treatment group, allowing for a randomized treatment comparison in the same patient population. Consistent with the observed exposure dependency, a significant treatment-by-baseline BMI (low ≤median vs high >median) interaction was also observed between patients for 24 W-CDP, where lighter patients received more benefit than heavier patients (Figure 1 ).

In ocrelizumab-treated patients with RMS, there was a trend of higher median B-cell levels during the double-blind period (DBP) being associated with greater rates of 24 W-CDP during the combined DBP and OLE (median circulating B-cell levels vs 0 cells/μL, HR [95% CI]: 1-5/μL, 1.36 [0.82-2.25] p = 0.23; >5/μL, 1.43 [0.79-2.62] p = 0.28) as well as during the OLE only (median circulating B-cell levels vs 0 cells/μL, HR [95% CI]: 1-5/μL, 1.31 [0.76-2.24] p = 0.36; >5/μL, 1.63 [0.88-3.03] p = 0.079; eFigure 1, links.lww.com/NXI/A801). In the DBP, when splitting ocrelizumab-treated patients with RMS at the median of the individual patient median B-cell levels (1 cells/μL; <median n = 305, ≥median n = 509) and comparing with IFN β-1a-treated patients (n = 829), patients with more B-cell depletion showed a greater reduction in risk of 24 W-CDP (HR [95% CI]: CD19 < median, 0.38 [95% CI: 0.21-0.68; p = 0.0011] vs IFN β-1a; CD19 ≥ median, 0.73 [95% CI: 0.51-1.05; p = 0.0881] vs IFN β-1a).

Composite Disability Progression

The ocrelizumab exposure dependency in 24 W-CDP (assessed by EDSS) was also observed in the composite measure of disability progression (cCDP) when comparing within ocrelizumabtreated patients (high vs low exposure; HR 0.64 [95% CI: 0.45-0.92; p = 0.0135]) and by ocrelizumab exposure quartile vs all IFN β-1a-treated patients (Figure 3 ). Among the subcomponents of 24 W-cCDP, an exposure trend was observed for T25FW (high vs low exposure; HR 0.70 [95% CI: 0.44-1.11; p = 0.1281]). There was no association between exposure and outcome observed for the 9HPT subcomponent.

Exposure dependency analysis of 24 W-cCDP was directionally consistent with RMS but did not reach statistical significance (high vs low exposure: HR 0.90 [95% CI: 0.70, 1.15; p = 0.39]). An exposure dependency trend on 24 W-cCDP was also observed across quartiles in patients with PPMS (Figure 3 ). In general, for the above measures, consistent results were also observed for 12-week confirmed data in patients with either RMS or PPMS (eTable 1, links.lww.com/NXI/A801).

Influence of Baseline Patient Characteristics

In RMS, all subgroups, with the exceptions of region the United States and EDSS ≥4, showed numerically greater reduction in risk of disability progression in the highexposure group compared with the low-exposure group in both the univariate and multivariate analyses (eFigure 2A and eTable 2, links.lww.com/NXI/A801). In the univariate subgroup analyses in PPMS, comparing the time to 24 W-CDP of ocrelizumab-treated patients with low and high exposures with all placebo patients, all subgroups with the exceptions of region the United States showed numerically greater or approximately identical reduction in risk of disability progression in the high-exposure group compared with the low-exposure group. Multivariate analysis results were consistent with the univariate analyses except for patients with a duration since symptom onset of ≤5 years, where the treatment effect in high-exposure patients with PPMS was markedly reduced (eFigure 2B and eTable 2, links.lww.com/NXI/A801). The interpretation of the multivariate analysis is limited by the small sample size.

Magnetic Resonance Imaging T1 Gadolinium-Enhancing Lesions and New and/or Enlarging T2 Lesions

Owing to the near-zero rate of T1 gadolinium-enhancing lesions with ocrelizumab treatment in patients with RMS or PPMS, exposure dependency could not be reliably assessed. For new and/or evolving T2 lesions, exposure dependency was evident for new and/or evolving T2 lesion rates in patients with RMS (high vs low exposure, RR [95% CI]: 0.46 [0.24-0.86] p = 0.0124) but not PPMS. Of note, the observed dependency in RMS was entirely driven by an increased lesion rate in the lowest exposure quartile.

Brain Atrophy

An exposure-dependent trend for whole brain volume change and an association with white matter volume change from rebaseline at week 24 to week 96, vs IFN β-1a, was seen in patients with RMS, with greater volume reduction at higher ocrelizumab exposure; no such associations were seen in patients with PPMS (Table 3 ). An exposure-dependent association with gray matter volume change from rebaseline at week 24 to week 96, vs comparator, was seen in patients with RMS and PPMS; however, less gray matter volume reduction was seen with higher ocrelizumab exposure (Table 3 ).

For the above measures, consistent results were also observed when the study baseline (week 0) was used for volumetric assessments in patients with either RMS or PPMS (eTable 3, links.lww.com/NXI/A801).

Safety Endpoints

No association between higher exposure and the incidence of SAEs, infections, serious infections, or infusion-related reactions was observed in either RMS or PPMS (Table 4 ).

Discussion

Ocrelizumab, the first anti-CD20 + B-cell-selective monoclonal antibody approved for the treatment of RMS and PPMS, at a dose of 600 mg IV every 6 months, had a significant benefit on disability progression in the pivotal phase 3 studies 2,3 and sustained efficacy and safety with continuous therapy up to 6.5-7 years in their OLEs. 4,5,11 In a prespecified subgroup-efficacy analysis of the pooled OPERA I/II studies, a significant treatment-by-subgroup interaction was observed between patients by baseline BMI for both 12 Wand 24 W-CDP, where benefits were evident across both subgroups vs IFN β-1a, but lighter patients received more benefit than heavier patients. 10 In this study, we report that higher ocrelizumab exposure, which leads to greater B-cell depletion in the blood, 9 was also associated with a reduced rate of disability progression. Disability may progress in MS because of both relapsing disease activity with incomplete recovery (relapse-associated worsening), and progression independent of relapse activity (PIRA). 6 We found that for most measures reflecting relapsing disease biology, including clinical (ARR) and MRI (new lesion) outcomes, no association with ocrelizumab exposure could be observed. This is potentially due to treatment-related reduction of these inflammatory pathology-related measures to such low levels that the effect size is no longer exposure-dependent (ceiling effect). An exception was seen for new and/or evolving T2 lesion rates in patients with RMS, possibly driven by an incomplete suppression of inflammation in the lowest exposure quartile, although the clinical relevance of differences between such low residual lesion rates at the boundaries of measurement sensitivity is uncertain.

3][14][15][16][17][18] At present, it is not known to what degree each of these pathologies contributes to progression in different patients and/or different stages of disease, and which components of this pathology may respond to higher ocrelizumab exposure specifically, although ocrelizumab favorably affects chronic-active evolving lesions. 19,20 The mostly statistically nonsignificant observations on different measures of brain volume loss are intriguing but could be dependent on methodologic constraints or differential effects on the gray and white matter compartments. An inverse exposure-response relationship was evident for white matter volume loss, perhaps through the strong reduction of lesion pathology and inflammatory processes by ocrelizumab that decreases the volume of white matter (pseudoatrophy). 21 On measures of disease progression (EDSS-based CDP, cCDP including T25FW measure of gait, and 9HPT of hand motor function) where the observed effects of ocrelizumab are statistically and clinically relevant but incomplete, we observed a consistent trend toward higher efficacy with higher drug exposure across the 3 studies in univariate and multivariate analyses. Owing to the strong effects of ocrelizumab on relapse prevention in RMS, the majority of disability progression was relapse-independent, 6 and when relapse-independent CDP (PIRA) was investigated separately here, similar associations were found (data not shown). In PPMS, the lack of statistical significance for the comparison in CDP and cCDP between high vs low exposure by median cut could be due to lower power (smaller sample size) or differences in the contributions of individual pathologies associated with progression. However, the highest exposure quartile was still associated with significant differences for both CDP and cCDP in PPMS.

As previously shown, the pharmacokinetics of ocrelizumab (measured in serum) can be accurately described by a 2-compartment pharmacokinetic model with time-dependent clearance, typical for an immunoglobulin G1 monoclonal antibody, 22 and with body weight as the main covariate. 9 reater B-cell depletion, and less B-cell repletion between doses, was observed in patients with higher ocrelizumab exposure. 9 It has previously been reported that repletion after anti-CD20 therapy is body surface area dependent, 23 and specifically after ocrelizumab therapy repletion was shown to be BMI dependent. 24 Other factors influencing the level of B-cell depletion with anti-CD20 therapies include the Fc-gamma receptor genotype, as described with rituximab. 25 ][28] IV vs subcutaneous dosing of anti-CD20 monoclonal antibodies show different pharmacokinetics (e.g., peak and mean blood concentration), which may manifest in differing clinical dynamic profiles. Only 2% of the body's total lymphocyte pool resides in peripheral blood, 29 and B-cell depletion in lymphoid organs is less complete than in blood. Furthermore, the relationship between blood and extravascular B-cell repletion kinetics is unclear, although preclinical data indicate repletion in the bone marrow and lymphoid tissue before the blood. 30 the present analysis, a consistent pharmacodynamic effect was observed in patients with RMS, where an incomplete B-cell depletion or higher B-cell counts in blood before the next infusion showed a trend toward elevated risk of disease progression over the DBP and OLE, and higher median B-cell levels during the 96-week DBP showed a trend for more disability progression in the OLE. This suggests that maintaining lower B-cell levels over a longer time may lead to better disability outcomes. In PPMS, these associations were not observed; however, this post-hoc analysis was not powered to detect an effect of B-cell lowering on progression in PPMS.

It is important that there was no association between ocrelizumab exposure and analyzed adverse events (SAEs, serious infections, and infusion-related reactions) in patients with RMS or PPMS.

The analyses presented here are subject to the limitations of any post hoc investigation, including sample and effect sizes. As noted, C mean was treated as a time-invariant measure because a patient's characteristics (e.g., body weight and sex) determining their pharmacokinetics are not expected to change during the course of the given observation period. The pharmacodynamics of ocrelizumab-mediated B-cell depletion are different compared with, e.g., drugs displaying a direct effect based on reversible receptor occupancy, which fluctuates in parallel to the pharmacokinetic profile. Owing to the mechanism of action of ocrelizumab, i.e., destruction of B cells, 2,3,9,30 B cells are depleted with immediate onset upon contact with ocrelizumab, but return only slowly, after regeneration from stem or progenitor cells in bone marrow. 31 he median time to B-cell repletion in blood was 72 weeks based on a lower limit of normal of 80 cells/μL, after dosing cessation. 9 B-cell depletion kinetics in other body compartments and particularly the CNS is less clear. However, this may affect clinical efficacy and could be linked to cumulative effects over time on B cells in blood and tissues because B-cell depletion becomes more pronounced in tissues with repeated ocrelizumab administrations. This could be a potential explanation for the exposure-dependent effects on long-term outcomes such as disability progression demonstrated in this study.

The observed differences in the demographic characteristics of sex and weight/BMI, when grouped by exposure quartile, were expected because these characteristics were identified as covariates in the population pharmacokinetic analysis, 9 and BMI was shown to affect disability outcome in a prespecified subgroup analysis for efficacy. 10 urthermore, although an association between ocrelizumab exposure quartile and efficacy on progression measures was observed, no causal dependence can be definitively concluded.

Treatment with ocrelizumab 600 mg is known to lead to rapid and near-complete depletion of B cells in blood, which is maintained over time with subsequent doses, 9 accompanied with a rapid suppression of acute disease activity (suppression of MRI activity within 4 weeks and relapse activity within 8 weeks). 32 It is, however, unclear to what extent efficacy and pathology track with levels of B cells in blood, and whether greater exposure and/or deeper depletion of B cells in tissue in the periphery and CNS is required to further modify disease and disability progression. The results from these post hoc exposure-response analyses suggest that a higher dose of ocrelizumab could lead to an improved efficacy on disability progression. However, the multivariate analysis did not identify whether this would benefit all or only subgroups of patients with MS. The absence of an increase of SAEs with higher ocrelizumab exposure encourages further exploration of the potential benefits of a higher dose in controlled prospective clinical studies. To this end, 2 double-blind, parallel-group, randomized phase 3b studies (one in RMS [MUSETTE; NCT04544436] and the other in PPMS [GAVOTTE; NCT04548999]) investigating the efficacy and safety of higher doses of ocrelizumab (1,200 mg for patients <75 kg or 1,800 mg for patients ≥75 kg, every 24 weeks) are ongoing and will inform whether higher ocrelizumab doses can further decrease the risk of disability progression.

Observational data from the OLE period of the phase 2 ocrelizumab trial indicated that both clinical relapses and new focal inflammatory lesions measured by MRI remain low even after some B-cell repletion occurs. 33 5][36] Some clinicians have interpreted these data to indicate that treatment intervals can be safely extended beyond the recommended 6-month schedule without any decrement in efficacy. The current data, indicating that higher serum levels of ocrelizumab were associated with improved efficacy against progression in both RMS and PPMS, strongly suggest that an every-6-month dosing schedule will provide better protection against disability progression than less frequent dosing.

In conclusion, higher ocrelizumab exposure and lower median B-cell levels in the blood were associated with a consistent and sustained benefit on rates of disability progression, across several outcome measures in RMS and, to some extent, PPMS. Higher ocrelizumab exposure and greater B-cell depletion may be important for the control of disability progression.

Acknowledgements

AcknowledgmentThe authors thank all patients, their families, and the investigators who participated in the trials contained within these analyses.The authors are grateful to Gisèle von Büren (F.Hoffmann-La Roche Ltd) for additional critical review of this manuscript and technical advice.Initial assistance and discussion regarding data and analyses was provided by Andrew Stead of Articulate Science, UK, and funded by F. Hoffmann-La Roche Ltd.The authors had full editorial control of the manuscript and provided their final approval of all content. Study FundingThis work was supported by financial support from F. Hoffmann-La Roche Ltd, Basel, Switzerland, for the study and publication of the manuscript.

Funding

funded by F. Hoffmann-La Roche Ltd.

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