Daratumumab in high-risk MGUS and low-risk smoldering myeloma: results of the Phase II D-PRISM study

Domain: neuroscience
Published: 2026-04-08
Editorial outcome: major_revision

Abstract
Daratumumab is approved for patients with multiple myeloma (MM) and high-risk
smoldering MM (HR-SMM). However, HR-SMM is often as genomically complex as MM,
suggesting it may be too advanced for single-agent intervention. We report on a Phase II
trial of single-agent daratumumab in patients with earlier-stage disease, including high-
risk monoclonal gammopathy of undetermined significance and low-risk SMM, to test if
earlier treatment can induce deep responses and prevent progression to MM (D-
PRISM/NCT03236428, n = 41). As primary outcome, the rate of Very Good Partial
Response or better is 17% (95% CI: 7-32), which is comparable to what was observed in
HR-SMM and does not meet the study’s primary endpoint. The overall response rate is
54%, with two patients developing MM and 51% biochemical progression. Grade 3 or
higher toxicities include hypertension (7%), diarrhea (2%), flu-like symptoms (2%), and
headache (2%). Genomic and immune variables associated with biochemical progression
are identified in exploratory analyses leveraging whole-genome and single-cell RNA-
sequencing. This study demonstrates that, although less effective than expected,
daratumumab is safe and can induce deep responses in certain early-stage patients,
highlighting the importance of adopting genomic and immune profiling to improve patient
selection and maximize the benefit/risk ratio in trials of early intervention.

Introduction
Precursor plasma cell disorders, including monoclonal gammopathy of undetermined
significance (MGUS) and smoldering multiple myeloma (SMM), exhibit a variable risk of
progression to symptomatic multiple myeloma (MM), ranging from 1% per year for MGUS
to up to ~50% in 2 years for patients with high-risk SMM (HR-SMM)1-5. MGUS is present
in approximately 4% of people over the age of 50, and has higher prevalence in older
individuals, Black individuals, and individuals with a family history of blood cancer1,2,4,6-11.
Features associated with high-risk MGUS (HR-MGUS) include non-IgG paraprotein,
serum M protein concentration of > 1.5 g/dl, and an abnormal free light chain (FLC) ratio,
and these patients carry a lifetime risk of progression to MM estimated at 37 - 58% at 20
years12,13. On the other hand, high-risk SMM can be defined by various criteria, including
the 2/20/20 model and the International Myeloma Working Group (IMWG) risk score
tool14. While low risk SMM (LR-SMM) patients may not be at immediate risk of
progression, approximately 50% will progress to overt MM at 10 years15. Additional high-
risk features that reflect disease biology, including cytogenetics, are currently under
investigation with promising results16-23.
Currently, the standard approach for patients with MGUS/SMM is observation until
progression24-26. However, early treatment with lenalidomide has shown benefit compared
to observation in two Phase III trials in patients with HR-SMM27-29. More recently, the
Phase III AQUILA trial demonstrated significant improvement in progression-free survival
(PFS) and overall survival (OS) with single-agent daratumumab compared to observation
in patients with HR-SMM30,31. On the basis of these results, daratumumab monotherapy
was recently approved for patients with HR-SMM in Europe and the US.
A key question remains whether the HR-SMM stage is already too advanced for a
single-drug intervention, as these patients exhibit genomic features that resemble those
seen in MM32-34. Several trials using intensive regimens in HR-SMM have failed to show
significantly different response rates compared to those observed in newly diagnosed MM
(NDMM). Examples of this include the GEM-CESAR trial, which studied the regimen of
carfilzomib, lenalidomide and dexamethasone (KRD) and autologous stem cell
transplantation in HR-SMM, and demonstrated a complete response rate (CR) of 64%35.
Similarly, a single-arm trial of KRD demonstrated a CR rate of 75.9% and a trial of
ixazomib, lenalidomide and dexamethasone demonstrated a CR rate of 31% in HR-
SMM36,37. This leads to the hypothesis that perhaps even earlier interventions at a lower-
risk disease state may be necessary to induce deeper responses and long-term remission
in certain patients with precursor conditions36,38. Another key challenge for the optimal
treatment of early-stage patients remains the identification of patients who are more likely
to benefit32-34,39. While the risk of progression of LR-SMM to overt myeloma is estimated
at 6.2% at 2 years per the 2/20/20 model, all patients with SMM carry a lifetime risk of
MM14. While there is general agreement that there is a need for tools that measure
disease biology and the state of the patient’s immune system in order to more accurately
predict who is likely to progress, it is not necessarily the case that those who are most
likely to progress when untreated are also the ones who are most likely to respond to
therapy, thus maximizing the benefit-risk ratio. For example, genomic variables that
predict a higher risk of progression to MM in patients with SMM, such as KRAS mutations,
are not predictors of response to therapy in patients with overt MM18,33. Therefore,
biomarkers to predict response to drugs, such as daratumumab, that may be used for
interception of progression in patients with SMM are needed to better drive clinical
decisions.
In this study, we aimed to assess whether single-agent daratumumab could induce
deep responses (i.e., Very Good Partial Response (VGPR) or better) and improve long-
term outcomes in patients with HR-MGUS and low-risk SMM (LR-SMM). Additionally, by
performing whole-genome sequencing (WGS) and single-cell RNA sequencing
(scRNAseq) of tumor and immune cells, we aimed to identify predictive biomarkers of
response to daratumumab monotherapy in early-stage patients, which following the
recent FDA approval may be critical for optimizing patient selection.

Results
Efficacy and safety of single-agent daratumumab in patients with HR-MGUS and
LR-SMM
Between January 2018 and February 2020, 41 patients were enrolled on this study and
received therapy (Figure 1A). Patient baseline characteristics are summarized in
Supplementary Table 1 and Figure 1B. Most patients (n=36/41; 88%) had LR-SMM,
and 5 patients (12%) had HR-MGUS. Per the 2/20/20 criteria for patients with SMM
(n=36), 22 patients had LR-SMM (54%), 12 had IR-SMM (29%), and 2 (5%) had HR-
SMM. In total, 39/41 patients (95%) completed 20 cycles of therapy as per the protocol.
Two patients discontinued therapy early due to withdrawal of consent (one after 6 cycles
and one after 16 cycles).
When considering FISH results obtained at baseline, primary cytogenetic
abnormalities were detected in only 16 out of 41 patients (39%). In contrast, all 19 patients
(100%, 95% CI: 82-100) profiled at baseline with scRNAseq of tumor cells (n=17) or WGS
(n=14) were successfully classified. Furthermore, scRNAseq and WGS detected
additional secondary high-risk abnormalities (1q+, n=1; del13q, n=4). To enable
cytogenetic analyses, we allowed extrapolation of FISH results from any point during the
course of disease for primary cytogenetic abnormalities and any point prior to treatment
administration for secondary abnormalities, and successfully classified a total of 38
patients (93%, 95% CI: 80-98). By combining all results, we classified a total of 39/41
patients (95%, 95% CI: 83-99), whom we could assess for high-risk cytogenetics (Figure
1B). High-risk cytogenetics, as defined by the IMWG (i.e., considering t(4;14), t(14;16),
1q+, and del13q), were present in 14/39 patients (36%, 95% CI: 22-53)14.
Adverse events are detailed in Table 1. The most common toxicities of any grade
were fatigue (n = 24/41; 59%), cough (n = 19/41; 46%), nasal congestion (n = 17/41;
41%), headache (n = 14/41; 34%), nausea (n = 13/41; 32%), and leukopenia (n = 13/41;
32%). Grade 3 or higher toxicities included hypertension (n = 3/41; 7%), diarrhea (n =
1/41; 2%), flu-like symptoms (n = 1/41; 2%), and headache (n = 1/41; 2%). Upper
respiratory infections (URI) occurred in 9 patients (22%), with 10% of patients developing
grade 2 URIs. Neutropenia was seen in 12 patients (29%), with 7 (17%) experiencing
grade 2 neutropenia. There were no grade 3 neutropenias or grade 3 infections. No
patients developed secondary hematologic malignancies at a median follow-up of ~5
years. One patient developed a new primary cancer (breast cancer).
The overall response rate (ORR) defined as partial response (PR) or better was
54% (n=22/41; 95% CI: 37-69%; 90% CI: 40-67%). Seven patients achieved a best
overall response of VGPR or better (17%; 95% CI: 7-32%; 90% CI: 8-30%). Best overall
responses were complete response (CR, n = 4/41; 10%; 95% CI: 3-23%), VGPR (n =
3/41; 7%; 95% CI: 2-20%), PR (n = 15/41; 37%; 95% CI: 22-53%), or minor response
(MR, n = 12/41; 29%; 95% CI: 16-46%) (Table 2, Figure 1C). Seven patients did not
respond.
Progression-free and overall survival post-treatment with daratumumab in patients
with HR-MGUS and LR-SMM
The median follow-up for all 41 patients was 63.5 months (range, 6.7-79.8). Median OS
was not reached (NR), and OS was 100% at 5 years of follow-up (Figure 2A). As of
December 2024, 25 patients remained on follow-up. Overall, two patients progressed to
MM and in both cases, progression was diagnosed based on the SLiM criteria (Figure
2B)5. One of the 2 patients was noted to have 60% plasmacytosis on their end of
treatment (EOT) BM biopsy and subsequently began induction therapy. The other patient
was noted to have a FLC ratio of >100 at follow-up visit 3 and began induction therapy.
No patients developed symptomatic MM.
Twenty-one patients (51%, 95% CI: 35-67) developSed biochemical progression
based on the IMWG criteria40. The median biochemical PFS was 59.5 (range: 5.5-76.3)
months (Figure 2C). Six patients developed biochemical progression while on therapy,
while 15 patients developed it after completing therapy, with four patients developing it
within 1 year of completing therapy. No patients discontinued trial therapy due to
progression. Biochemical progressors demonstrated continuous gradual increase in M-
spike levels and involved:uninvolved FLC ratios over time (Figure 2D,E).
The median duration of response for patients who achieved PR or better was 64.8
months (Figure 2F). Out of the 21 patients who developed biochemical progression, one
patient started therapy on an HR-SMM protocol as they subsequently met 2/20/20 criteria
for HR-SMM, while another patient met the SLiM criteria for progression, as described
above, and began induction therapy. Nineteen patients had not started subsequent
therapy at the time of their last follow-up.
Depth of response and high-risk cytogenetics associated with biochemical PFS in
response to daratumumab
Next, we searched for variables that can predict biochemical PFS in our patients. There
was no difference in biochemical PFS by stage (HR-MGUS vs LR-SMM, two-sided log-
rank, p=0.66; 2/20/20 HR-SMM vs LR-SMM, p=0.45; 2/20/20 HR-SMM vs IR-SMM,
p=0.48) and neither M-spike levels nor BM infiltration were associated with biochemical
PFS on univariate analysis (p=0.22 & p=0.39, respectively)14. While there was no
difference in SLiM-CRAB PFS, biochemical PFS was significantly longer in patients who
achieved VGPR or better (NR vs 52.2 months; two-sided log-rank, p=0.014) and duration
of response was also longer, although this comparison did not reach statistical
significance (two-sided log-rank, p=0.075) (Figure 3A-C).
While the impact of high-risk cytogenetics, as defined by the IMWG, on SLiM-
CRAB PFS could not be assessed due to low power, biochemical PFS was significantly
longer in patients with SMM and standard vs high-risk cytogenetics by IMWG (NR vs 49.2
months; two-sided log-rank, p=0.037) (Figure 4A,B). To determine if other cytogenetic
abnormalities may be more predictive in the setting of daratumumab monotherapy, we
tested recurrent abnormalities that were present in at least 2 patients (Figure 4C).
Interestingly, we found that the presence of t(11;14) was associated with significantly
longer biochemical PFS (two-sided Wald p = 0.016 & two-sided log-rank p=0.0029)
(Figure 4D). In contrast, the presence of t(4;14) was associated with shorter biochemical
PFS (two-sided Wald p=0.0046 & two-sided log-rank p < 0.001) (Figure 4E). The
presence of t(4;14) is considered a high-risk factor in both treatment-naïve patients with
SMM, as well as patients with overt MM who receive therapy. On the other hand, the
presence of t(11;14) is not associated with superior outcomes in treatment-naïve patients
with SMM or patients with overt disease who receive therapy. Thus, the observed
association of t(11;14) with response to daratumumab may be related to its administration
as monotherapy instead of in combination with other agents or its administration earlier
on in the course of disease.
Single-cell RNA sequencing reveals immune biomarkers of response to
daratumumab monotherapy in patients with HR-MGUS and LR-SMM
To explore how the immune system may influence response to daratumumab
monotherapy in this patient population, we performed scRNAseq on 48 CD138-negative
and 18 CD138-positive BM mononuclear cell samples from 36 patients (biochemical
progressors (P), n=18; non-biochemical progressors (NP), n=16; patients who
discontinued treatment, n=2). Another 6 patients (P, n=3; NP, n=3) also had samples
drawn at EOT to monitor immune cell dynamics post-therapy (Supplementary Table 2).
Notably, among progressors, 8 patients progressed within ~24 months from treatment
initiation (early progressors), while the remaining patients (n=10) progressed after ~45
months (late progressors). In total, we profiled 71,771 BM immune cells, including 37,734
T cells, 10,338 NK cells, 5,422 B cells, 16,277 monocytes, and 2,000 dendritic cells
(Figure 5A).
First, we compared the proportions of all immune cell types (n=20) between
progressors (n=18) and non-progressors (n=16). Interestingly, biochemical progressors
had significantly higher proportions of CD56dim NK cells at baseline compared to non-
progressors (two-sided Wilcoxon rank-sum, q=0.0364) (Figure 5B). No such difference
was observed between early vs late progressors (p=0.275). To ensure our results were
not confounded by differences in target antigen expression by tumor cells, we compared
the proportion of CD38-expressing (>0.1) tumor cells between groups and observed no
association with biochemical progression (two-sided Wilcoxon rank-sum, p=0.613)
(Figure 5C). Furthermore, no significant difference in tumor burden was observed
between progressors and non-progressors (two-sided Wilcoxon rank-sum, p=0.644 and
p=0.581 for BM infiltration and M-spike, respectively). Lastly, and in line with prior
observations, the proportion of CD38-expressing (>0.1) CD56dim NK cells decreased
significantly post-treatment (two-sided Wilcoxon signed-rank, p=0.00216), but with no
difference between progressors (n=3) and non-progressors (n=3), suggesting that NK cell
fratricide due to CD38 expression may not be associated with response in this setting
(Figure 5D)41.
To understand how the baseline phenotype of CD56dim NK cells differs between
progressors and non-progressors, we performed differential expression analysis after
downsampling to ensure equal numbers of cells were contributed by each patient within
each group and equal numbers of cells were compared across groups (P, n=18; NP,
n=11; 396 cells per group). We observed significantly higher levels of FCER1G in
CD56dim NK cells of non-progressors compared to progressors and in late compared to
early progressors (two-sided Wilcoxon rank-sum, q < 0.05) (Figure 5E,F).

Methods
D-PRISM is a single-arm, Phase II study using single-agent daratumumab in patients with
HR-MGUS and LR-SMM (D-PRISM; NCT03236428, posted 1 August 2017). The trial
protocol was approved by the Dana-Farber/Harvard Cancer Center Institutional Review
Board (#17-212) and is provided in the Supplementary Information file. Patient samples
were banked under this protocol for correlative studies. All participants provided written
informed consent in accordance with the Declaration of Helsinki. Patient selection was
blind to the participant’s sex and gender.
Eligibility Criteria
Eligibility criteria for patients with HR-MGUS included <10% plasmacytosis and < 3 g/dL
M-spike in the serum along with at least 2 of the following 3 criteria: abnormal serum FLC
ratio (<0.26 or > 1.65), M protein ≥ 1.5 g/dL or non-IgG M protein (including IgA). Low-
risk SMM was defined as having only 1 of the following criteria: monoclonal protein ≥ 3
g/dL, ≥ 10% BM plasmacytosis, or sFLC ratio < 0.125 or > 8. Patients who met SLiM-
CRAB criteria were excluded5.
Treatment Regimen
A treatment cycle was defined as 4 weeks in length. All patients received daratumumab
dosed at 16 mg/kg intravenously for each four-week cycle for up to 20 cycles. During
Cycles 1 and 2, patients received daratumumab weekly. During cycles 3 through 6,
daratumumab was administered every 2 weeks. During cycles 7 through 20,
daratumumab was administered every 4 weeks. Assessments of disease and progression
were performed at the beginning of each cycle, at the end of treatment, and every 3 or 6
months thereafter. Patients were to be followed for up to five years after the
discontinuation of therapy.
Objectives and End Points
The primary objective of this trial was to determine the proportion of patients who achieve
VGPR or better after 20 cycles of therapy. Response was determined according to the
IMWG criteria52. Secondary objectives included the following: 1) assess the duration of
response; 2) assess the safety of the agent in this patient population; 3) assess if baseline
immune features can predict response or progression, 4) assess changes in the immune
microenvironment in HR-MGUS and LR-SMM patients during the study; 5) assess the
association between immune changes and progression to SMM or MM; and 6) assess
the rate of secondary hematologic malignancies.
Statistics & Reproducibility
The study aimed to enroll 50 patients, however due to the COVID-19 pandemic that
occurred during the trial enrollment period, enrollment was ended early with 41 patients
enrolled. The study was not randomized and thus, the investigators were not blinded.
According to the study protocol, the criterion to determine whether the treatment is
promising was for the lower limit of the two-sided 90% binomial confidence interval for the
deep response rate (i.e., VGPR or better) to be at least 50%. In practice, both 90%
confidence intervals and 95% confidence intervals were reported for ORR and the rate of
VGPR or better. Patients who received any amount of study treatment were evaluable for
safety and toxicity analyses from the time of their first dose. Patients who had measurable
disease, received at least one cycle of therapy, and had their disease re-evaluated were
considered evaluable for response. Patients who showed objective disease progression
prior to removal from the study were also considered evaluable.
No data was excluded from analysis, unless explicitly stated in the manuscript and
figure legend. For example, analyses on genomic biomarkers of progression were
conducted in patients with SMM who had cytogenetic data available, thus excluding
patients with MGUS and a single patient with SMM and no cytogenetic information.
Progression-free survival was measured from the date of registration to the date
of documentation of progressive disease (SLiM-CRAB or biochemical progression) or
death from any cause and censored for those alive and free from progression. According
to the SLiM-CRAB criteria, a diagnosis of MM was made if ≥ 60% clonal plasma cells
were detected in the BM, the involved:uninvolved FLC ratio was ≥ 100, >1 focal lesion
was detected on MRI, or patients developed CRAB symptoms5. Time-to-event endpoints
were estimated using the Kaplan-Meier method. Median follow-up was calculated using
the reverse Kaplan-Meier method. Clinical responses to study treatment were reported
as proportions with 95% exact binomial confidence intervals. Continuous measures were
summarized by their median and range, and categorical variables were summarized as
proportions. Response outcomes and other categorical variables were tested for
association with continuous variables using two-sided Wilcoxon rank-sum tests or to other
categorical variables using two-sided Fisher’s exact tests. Statistical analyses of clinical
data were performed using R (v4.4.2; 2024-10-31).
No sex-based or gender-based analyses were conducted in this study, as such
analyses were not part of the study protocol. Self-reported sex information is available for
participants in the scRNAseq cohort in the study’s dbGaP site (for access to dbGaP,
please, see Data Availability).
Non-preplanned exploratory outcomes
Single-cell RNA sequencing (scRNAseq) data and analysis
Bone marrow (BM) aspirates from 36 patients enrolled on the trial were collected at
baseline (n=36) and EOT (n=6). Bone marrow mononuclear cells were isolated using
Ficoll and subjected to CD138 selection using AutoMACS (Miltenyi), followed by
cryopreservation in Fetal Bovine Serum (FBS), supplemented with 10% Dimethyl
Sulfoxide (DMSO). Cryopreserved CD138-negative cells (n=48) from 36 individuals and
CD138-positive cells (n=18) from 17 individuals were thawed and encapsulated on a
Chromium Controller, according to the manufacturer’s instructions (10X Genomics).
Gene expression libraries were prepared using Chromium Next GEM Single Cell 5’
Reagent Kits (v2, Dual Index) and Library Construction Kits (10X Genomics). For tumor
samples, B cell receptor (BCR) libraries were also constructed using Chromium Single
Cell Human BCR Amplification Kits and Library Construction Kits, according to the
manufacturer’s instructions (10X Genomics). Libraries were sequenced on NovaSeq
S6000 instruments at the Genomics Platform of the Broad Institute of MIT and Harvard
(Cambridge, MA).
FASTQ files were demultiplexed, and count matrices were produced using
CellRanger (v6.0.1), and downstream analyses were conducted using R (v4.2.2) and
Seurat (v5.1.0)53,54. Immune cells were annotated using established immune cell
expression markers and differential expression analysis, as is standard in the
field44,45,55,56. Red blood cells and plasma cells identified in the CD138-negative samples
were discarded, resulting in a total of 20 immune cell types used for downstream
analyses. Tumor cells were identified on the basis of expressing markers of malignancy
(e.g., NCAM1, CCND1, etc.) and exhibiting monoclonal expansion in the BCR data44,56-
58.
Immune cell proportions were computed by dividing the cell count of a cell type in
a sample by the sample’s total immune cell count. Two patients who discontinued
treatment were excluded from downstream analyses related to progression. The
remaining patients had at least 200 immune cells detected and were included in
downstream analyses (n=34). Immune cell proportions for all cell types (n=20) were
compared between biochemical progressors (n=18) and non-progressors (n=16), or early
(n=8) and late biochemical progressors (n=10), using two-sided Wilcoxon rank-sum tests,
and p-values were adjusted using the Benjamini-Hochberg method (a=0.05). The
proportion of CD38-expressing tumor cells and CD56dim NK cells was determined by
computing the proportion of cells with normalized CD38 expression > 0.1. For 6 patients
with EOT samples available, the proportion of CD38-expressing CD56dim NK cells was
compared between baseline and EOT timepoints by a two-sided paired Wilcoxon signed-
rank test.
Differential expression analysis was conducted using two-sided Wilcoxon rank-
sum tests to compare the baseline expression profile of CD56dim NK cells between
biochemical progressors (n=18) and non-progressors (n=11), or early (n=8) and late
biochemical progressors (n=10). Only patients with at least 20 CD56dim NK cells at
baseline were considered for these analyses. To balance the number of cells compared
between groups as well as the number of cells contributed by each individual, we
downsampled 396 cells per group for biochemical progressors (18 patients, 22 cells each)
versus non-progressors (11 patients, 36 cells each) analysis and 280 cells per group for
early (8 patients, 35 cells each) versus late biochemical progressors (10 patients, 28 cells
each) analysis. Lastly, we filtered for genes with more than 3 counts in at least 10 cells.
P-values were adjusted using the Benjamini-Hochberg method (a=0.05).
Whole genome sequencing (WGS) of tumor samples
Whole genome sequencing was performed on bone marrow CD138+ cells (tumor) and
matched peripheral blood mononuclear cells (PBMC; normal). Genomic DNA was
extracted using the Monarch Genomic DNA Purification Kit (New England Biolabs), and
libraries were prepared using the NEBNext Ultra II FS DNA Library Prep Kit (New England
Biolabs) with unique dual-index adapters (NEBNext Multiplex Oligos) and sequenced at
the Genomics Platform of the Broad Institute of MIT and Harvard (Cambridge, MA).
Sequencing reads were aligned to GRCh38, and the Getz Lab WGS processing and
analysis pipeline was deployed, as previously described33,59.
Fluorescence in situ hybridization (FISH) and cytogenetic classification analyses
Results from clinical-grade FISH testing were extracted from medical records and
reviewed for accuracy by three independent data collectors. To maximize the contribution
of FISH to our cytogenetic classification, we allowed extrapolation of FISH results for
primary cytogenetic abnormalities only (i.e., patients were considered positive for primary
IgH translocations and hyperdiploidy, if they were positive by FISH at any point during the
course of disease). In contrast, patients were considered positive for secondary
cytogenetic abnormalities (gain or amplification of chr1q/1q+, del13q, and del17p), if a
positive FISH result was obtained at baseline or prior to that. Positive results for
secondary abnormalities that were obtained after treatment administration were not
considered to account for the possibility of a newly acquired secondary abnormality.
To identify cytogenetic biomarkers of biochemical progression, we combined
extrapolated FISH results with results from scRNAseq and WGS (which were conducted
on tumor cells from a total of 19 patients who had tumor cells available for testing). We
restricted this analysis to patients with SMM and cytogenetic classification (n=35) and
tested only abnormalities that were present in at least 2 patients (primary: t(11;14), t(4;14),
t(14;16), hyperdiploidy; secondary: 1q+, del13q, del17p) using Cox regression and two-
sided Wald tests. Kaplan-Meier analyses with two-sided log-rank tests were also
conducted for cytogenetic abnormalities with a two-sided Wald p < 0.05.

Peer review rounds
[{"round": 1, "reviewer_comments": {"reviewer_1": "In this study by Nadeem et al, the investigators tried to address whether early intervention with daratumumab can improve\noutcomes in patients with high-risk monoclonal gammopathy of undetermined significance (HR-MGUS) and low-risk\nsmoldering multiple myeloma (LR-SMM). The authors enrolled 41 patients and achieved a 54% overall response rate with\n17% deep responses. At a median follow-up of ~5 years, 2 patients (~5%) progressed to MM.\nFirst, I have the following major concerns regarding the overall study design:\n1. The primary endpoint of this trial is not clinically meaningful. The hematologic response assessment in multiple myeloma\nas per the IMWG criteria has never been validated in this population (HR-MGUS and LR-SMM). As the authors themselves\nshow in Figure 3 (A and B), achieving VGPR or better was not significantly associated with SLiM-CRAB PFS despite long\nfollow-up. It was only associated with biochemical PFS, the clinical importance of which is unclear in this population.\n2. The authors have devised a cytogenetic risk score for biochemical PFS. I would strongly suggest to remove it from the\nmanuscript due to the following reasons:\na) The outcome being predicted by this risk score is not clinically meaningful.\nb) This dataset is not powered for any multivariable analysis, and the best practices for devising a clinical risk prediction\nscore (e.g. taking all available important variables into account, assessing discrimination and calibration etc.) were not\nfollowed.\nThe authors can simply report descriptively the prognostic impact of each cytogenetic abnormality on univariate analysis.\nOther major comments:\n1. The authors must clearly state in the abstract and the 1st paragraph of the discussion that the study failed to achieve its\nprimary endpoint.\n2. Two patients in this cohort progressed to MM, both based on SLiM criteria. In the patient with sFLC ratio>100, was a 24\nhour urine Bence Jones protein obtained at baseline prior to induction therapy? If so, please provide that information.\n3. The authors should provide data on the time-interval between date of original diagnosis of HR-MGUS/LR-SMM and\nenrollment in this trial.\nMinor comments:\n1. In the introduction, the authors should clarify what is the expected risk of progression to MM in patients with HR-MGUS\nand LR-SMM as the criteria used in this trial.\n2. In the discussion (Page 6-7), the authors state that “Here, we demonstrated for the first time that depth of response also\nmatters in patients with a lower risk of progression, and therefore, this should be considered in the end-points of future\nclinical trials of SMM.” I think this is extremely premature, and is not borne out of the data presented in this trial, which shows\nthat depth of response was only correlated with biochemical PFS but not SLiM-CRAB PFS.", "reviewer_2": "Nadeem and colleagues present a nicely conducted and important phase II study on HR-MGUS and LR-SMM. The study is\ndesigned well and the results, including state of the art sequencing and immune subset analyses, are presented clearly.\nThis trial follows on a series of trials investigating daratumumab monotherapy in myeloma precursor conditions but it\nspecifically focuses on LR-SMM/HR-MGUS. Further, it follows a series of important studies from Irene\nGhobrial and DFCI colleagues on therapeutic interventions in myeloma precursors. I have some comments:\nIntroduction:\n- Please calrify/elaborate a little on the first half of this sentence: „Several trials using three or four-drug intensive regimens\nhave failed to show significantly higher response rates compared to those observed in newly diagnosed MM,…“\nResults:\n- Please remove: „and not due to toxicity“, it is redundant.\n- What were the reasons that FISH was detected in only 16 out of 41 patients.\n- Please state whether ISR/IRR were observed.\n- What ist he authors explanations that no grade 3/4 neutropenia rates were observed.\n- Please add information on which induction therapy was started in the 2 patients progressing with SLiM criteria. Was a anti-\nCD38 mAB used? How was response? Did they recieve ASCT? Any genomic insights on these two patients?\n- Figure 1B: there is a color code for „cytogenetics“ but I cannot see the respective column in the graph above. Is it similar\nwith „high risk genomics“? If so, I would suggest to split up genomics (ie. Sequencing) and FISH.\n- Is it possible to look at the M-protein / involved FLC kinetics in patients with biochemical progression?\n- Please state clearly which patients progressed on treatment vs. After 20 cycles. Among those with progression after 20\ncycles, which patients were early progressors wihtin 0-6 or 0-12 months? I suggest to also update in Figure 1A (consort) the\npatients who discontinued the treatment due to PD (please also consult the CONSORT guidelines here)\n- I would suggest to clarify in the caption of Table 1 how high risk cytogenetics was defined. Please also define 2/20/2 4-\nfactor HP, I think it refers tot he continuous IMWG 2020 model?\n- Can you add information, how a pretreated LR SMM patient could receive treatment in a HR-SMM trial (maybe add the trial\nnumber).\n- Please clarify in the results text that you refer to high risk according to IMWG 2020 model (Fig4 A+B).\n- The paragraph on the new defintion of high risk cytogenetics is not clear. What do you mean by „empirically based“ here?\nIs there a reference? And were does the evidence come from to sum up scores based on the number of aberrations? In R2-\nISS this is possible, but it does not include del13q.\n- How was „tumor burden“ defined? „Furthermore, no significant difference in tumor burden was observed between\nprogressors and non-progressors…“\nMethods:\n- Why was daratumumab given intravenously? (and not subcutaneously?)\n- Eligibility criteria and response assessment: IMWG response criteria rely on a stepwise approach of measurable disease\n(secretory, low secretory etc; see 2016 paper). Please add details on which patients had measurable or low secretory\ndiesase etc. according ton IMWG criteria. Did this impact the actual depth of response in this study?\n- Please clarify if response rates are confirmed response according to IMWG 2016 criteria.\n- Please clarify whether regular imaging PET-CT or MRI was part of the follow up (and how frequently).\n- The eligibilty criteria are very condensed in the study protocol. Can you clarify that monoclonal protein (in case of MGUS or\nSMM) or clonal plasma cells (in case of SMM) had tob e present for inclusion in the trial.\n- The LR_SMM definition is debatable in my opinion. How is your LR_SMM definition justified empirically? As an example, a\npatient with m protein 10 g/l, FLC ratio 7, BMPC 30% + deletion 17p could have been included in your trial, though I (and\nyou probably as well) would not consider this LR.\n- Can you please provide a data sharing statement for the clinical data as well.\nDiscussion:\n- Lines 237ff: BM infiltration can is highly variable across the skeleton, this spatial heterogeneity should be mentioned here\nas well. As such, I am not sure if BMPC is a reliable surrogate of tumor burden", "reviewer_3": "This is a small well performed single arm phase II study of daratumumab treatment for SMM. The point is that daratumumab\nhas recently been approved for SMM treatment and they attempt to describe its activity in LR SMM and HR MGUS.\nTo aid in this utility they apply a novel score they have developed. The study is interesting and well performed. The results may help\nin the clinical use of daratumumab for myeloma precursor conditions.", "reviewer_4": "This manuscript presents the results of a well-conducted clinical study evaluating daratumumab in patients with high-risk\nMGUS and low-risk SMM, with a particular focus on early intervention and its potential to delay progression. The overall\ndesign is sound, the statistical methodology is generally appropriate, and the study provides valuable insights into this\npatient population. My comments below focus mainly on statistical methodology and its reporting, as this is crucial for\nreproducibility and for allowing readers to properly interpret the study outcomes.\n1. For the evaluation of ORR, you used a two-sided 90% confidence interval. Please specify the two-sided significance level\nused in the power calculation for the statistical method. If it exceeds 5%, please explain the reason for this choice.\nAdditionally, please justify why 95% confidence intervals were used for endpoints other than ORR, given that ORR is the\nprimary efficacy endpoint.\n2. In Figure 5, although the statistical methods section does not mention it, you appear to have applied a Benjamini–\nHochberg procedure for multiple-comparison adjustment. Please clarify for which specific set of multiple tests this correction\nwas applied, and explicitly state the significance level used after adjustment.\n3. In Figure 5B, the notation “q” is used — is this intended to denote an adjusted p-value (i.e., q-value from FDR correction)?\nPlease clarify.\n4. The manuscript mentions 95% confidence intervals for the Kaplan–Meier curves. Please indicate clearly where these\nintervals were actually used in the analysis or figures, and revise the statistical methods section to focus on the analyses that\nwere actually performed in this study."}, "author_response": "We would like to sincerely thank our reviewers for their feedback, which we believe has\nimproved the quality of our manuscript. Specifically, our revised manuscript now leverages the\ncytogenetic variables that associate with biochemical progression in our cohort; additionally, it includes figures\nvisualizing the progressive increase in M-spike and FLC ratio values in biochemical progressors,\nas well as a supplemental table with outcome and toxicity data in the trial.\nPlease, see below for a point-by-point response to reviewer comments, which have been copy-\nedited for typos:\nReviewer #1 (Remarks to the Author):\nIn this study by Nadeem et al, the investigators tried to address whether early intervention with\ndaratumumab can improve outcomes in patients with high-risk monoclonal gammopathy of\nundetermined significance (HR-MGUS) and low-risk smoldering multiple myeloma (LR-SMM).\nThe authors enrolled 41 patients and achieved a 54% overall response rate with 17% deep\nresponses. At a median follow-up of ~5 years, 2 patients (~5%) progressed to MM.\nFirst, I have the following major concerns regarding the overall study design:\n1. The primary endpoint of this trial is not clinically meaningful. The hematologic response\nassessment in multiple myeloma as per the IMWG criteria has never been validated in this\npopulation (HR-MGUS and LR-SMM). As the authors themselves show in Figure 3 (A and B),\nachieving VGPR or better was not significantly associated with SLiM-CRAB PFS despite long\nfollow-up. It was only associated with biochemical PFS, the clinical importance of which is unclear\nin this population.\nWe thank the reviewer for expressing this concern. It is common to adopt the IMWG\nresponse criteria from multiple myeloma when designing clinical trials in the precursor disease\nsetting, precisely because this is a new setting to be conducting a trial in and no set of criteria has\nbeen established yet. This is similar to what was previously done in high-risk SMM studies. As\nsuch, validating the utility of IMWG response criteria in an even earlier disease setting was part\nof what we set out to do with this study.\nAt this time, and given the relatively slower progression in patients with HR-MGUS and LR-SMM,\nthe follow-up is not long enough to perform analyses related to SLiM-CRAB progression; case in\npoint, only 2 individuals in our cohort developed SLiM-CRAB events within our follow-up period.\nAs such, SLiM-CRAB analyses are difficult to interpret. This is also why we primarily focused on\nbiochemical progression in the present manuscript, for which we are currently powered to conduct\nanalyses.\nAs soon as the data matures further in a few years, we plan to conduct SLiM-CRAB analyses,\nwhich should offer some more clarity on the utility of IMWG response criteria in this clinical setting\nand in relation to SLiM-CRAB progression. Until then, however, and to enable the field to continue\nmaking progress, we believe that biochemical progression analyses are relevant and important\nto share with the community as early as possible.\n2. The authors have devised a cytogenetic risk score for biochemical PFS. I would strongly\nsuggest to remove it from the manuscript due to the following reasons:\na) The outcome being predicted by this risk score is not clinically meaningful.\nb) This dataset is not powered for any multivariable analysis, and the best practices for devising\na clinical risk prediction score (e.g. taking all available important variables into account, assessing\ndiscrimination and calibration etc.) were not followed.\nThe authors can simply report descriptively the prognostic impact of each cytogenetic abnormality\non univariate analysis.\nWe thank the author for their feedback. We have removed the multivariate analysis\ncomponent and are now simply reporting on univariate associations for cytogenetic variables that\noccur in at least 2 patients (Revised manuscript, p. 5 & Fig. 4C-E).\nOther major comments:\n1. The authors must clearly state in the abstract and the 1st paragraph of the discussion that the\nstudy failed to achieve its primary endpoint.\nWe have now implemented this suggestion and the revised manuscript states that the\nprimary endpoint was not achieved both in the abstract (Revised manuscript, p. 2) and in the\ndiscussion (Revised manuscript, p. 6).\nFor example, our Discussion now reads:\n“Although the rate of VGPR or better was expected to be higher at the time this trial was\ndesigned and the primary end point was not achieved, it is in line with the response rates reported\nsince in the Phase III AQUILA trial of daratumumab monotherapy in patients with HR-SMM (ORR\nof 63.5%, VGPR or better of 29.9%) and the Phase II CENTAURUS trial of daratumumab\nmonotherapy in patients with IR-SMM/HR-SMM (ORR of 56.1%, VGPR or better of 29.3%)31,41,42”.\n2. Two patients in this cohort progressed to MM, both based on SLiM criteria. In the patient with\nsFLC ratio>100, was a 24-hour urine Bence-Jones protein obtained at baseline prior to induction\ntherapy? If so, please provide that information.\nThis patient did have a 24-hour urine test prior to beginning induction therapy, which\nrevealed 294 mg/dl of Bence-Jones proteinuria, further confirming the patient was progressing.\n3. The authors should provide data on the time-interval between date of original diagnosis of HR-\nMGUS/LR-SMM and enrollment in this trial.\nWe thank the reviewer for their suggestion. The median distance between the date of\ndiagnosis and date of registration was 190 days or ~6 months (IQR, 111-412 days).\nMinor comments:\n1. In the introduction, the authors should clarify what is the expected risk of progression to MM\nin patients with HR-MGUS and LR-SMM as the criteria used in this trial.\nThis information has now been added to the introduction section of the revised manuscript\n(Revised manuscript, p. 3):\n“Features associated with high-risk MGUS (HR-MGUS) include non-IgG paraprotein, serum M\nprotein concentration of > 1.5 g/dl, and an abnormal free light chain (FLC) ratio, and these patients\ncarry a lifetime risk of progression to MM estimated at 37 - 58% at 20 years. On the other hand,\nhigh-risk SMM can be defined by various criteria, including the 2/20/20 model and the\nInternational Myeloma Working Group (IMWG) risk score tool. While low risk SMM (LR-SMM)\npatients may not be at immediate risk of progression, approximately 50% will progress to overt\nMM at 10 years.”\n2. In the discussion (Page 6-7), the authors state that “Here, we demonstrated for the first time\nthat depth of response also matters in patients with a lower risk of progression, and therefore, this\nshould be considered in the end-points of future clinical trials of SMM.” I think this is extremely\npremature, and is not borne out of the data presented in this trial, which shows that depth of\nresponse was only correlated with biochemical PFS but not SLiM-CRAB PFS.\nWe thank the reviewer for their feedback. We have now amended this sentence to\nhighlight that our data pertains to biochemical PFS and that an association with SLiM-CRAB PFS\nhas not been demonstrated yet (Revised manuscript, p. 7).\n“Here, we demonstrated for the first time that deeper responses can predict longer biochemical\nPFS in patients with early-stage disease and it remains to be seen whether IMWG response\ncriteria can also predict SLiM-CRAB PFS in this setting.”\nReviewer #2 (Remarks to the Author):\nNadeem and colleagues present a nicely conducted and important phase II study on HR-MGUS\nand LR-SMM. The study is designed well and the results, including state of the art sequencing\nand immune subset analyses, are presented clearly. This trial follows on a series of trials\ninvestigating daratumumab monotherapy in myeloma precursor conditions but it specifically\nfocuses on LR-SMM/HR-MGUS. Further, it follows a series of important studies from Irene\nGhobrial and DFCI colleagues on therapeutic interventions in myeloma precursors. I have some\ncomments:\nIntroduction:\n- Please, clarify/elaborate a little on the first half of this sentence: “Several trials using three or\nfour-drug intensive regimens have failed to show significantly higher response rates compared to\nthose observed in newly diagnosed MM,…”.\nWe have now clarified that the multi-drug regimen trials we were referring to were\nconducted in patients with high-risk SMM and provided additional information on these trials\n(Revised manuscript, p. 3).\n“Several trials using intensive regimens in HR-SMM have failed to show significantly different\nresponse rates compared to those observed in newly diagnosed MM (NDMM). Examples of this\ninclude the GEM-CESAR trial34, which studied the regimen of carfilzomib, lenalidomide and\ndexamethasone (KRD) and autologous stem cell transplantation in HR-SMM, and demonstrated\na complete response rate (CR) of 64%. Similarly, a single arm trial of KRD35 demonstrated a CR\nrate of 75.9% and a trial of ixazomib, lenalidomide and dexamethasone36 demonstrated a CR rate\nof 31.% in HR-SMM.”\nResults:\n- Please remove: “and not due to toxicity“, it is redundant.\nThis part has now been removed.\n- What were the reasons that FISH was detected in only 16 out of 41 patients?\nDue to lower tumor burden in this patient population, most patients showed insufficient\nplasma cells in their bone marrow aspirate at baseline, and therefore FISH could not be\nperformed, although it was ordered and attempted as per clinical standards. Additionally, in 2\npatients, FISH was conducted but was negative for any primary abnormalities, and in 3 cases,\nFISH did not determine the type of IgH translocation present in the sample. For these reasons,\ncanonical primary cytogenetic abnormalities (i.e., hyperdiploidy or IgH translocations) were\ndetected in only 16 patients at baseline.\n- Please, state whether ISR/IRR were observed.\nThis is reported in Table 2. In total, seven patients experienced an IRR.\n- What is the authors’ explanation that no grade 3/4 neutropenia rates were observed?\nWhile the mechanism behind high-grade neutropenia post-daratumumab is unclear, we\nspeculate that high-grade neutropenia was not observed in this population post-therapy, perhaps\ndue to low-risk disease and an otherwise healthier bone marrow microenvironment.\n- Please, add information on which induction therapy was started in the 2 patients progressing\nwith SLiM criteria. Was an anti-CD38 mAB used? How was response? Did they receive ASCT?\nAny genomic insights on these two patients?\nOne patient received induction therapy on a clinical trial of daratumumab, ixazomib, lenalidomide\nand dexamethasone. They achieved a partial response and have remained on therapy without\nsigns of progression at the time of last follow-up. This patient was transplant-ineligible, hence did\nnot receive Autologous Stem Cell Transplantation (ASCT). The other patient was treated at an\noutside institution and further details about the induction regimen and response to therapy are\nunavailable.\n- Figure 1B: there is a color code for “cytogenetics” but I cannot see the respective column in the\ngraph above. Is it similar with “high risk genomics”? If so, I would suggest to split up genomics\n(i.e., Sequencing) and FISH.\nWe thank the reviewer for their suggestion. We have now revised our manuscript to use\nthe 2020 IMWG criteria for high-risk cytogenetics throughout. While our main figure (Revised\nManuscript, Figure 1B) summarizes cytogenetic results across clinical-grade FISH and\nresearch-level assays, we have provided here a figure that separates clinical-grade FISH results\nat baseline from research-level results (Response to Reviewers, Figure 1).\nResponse to Reviewers Figure 1. Heatmap of cytogenetic information in the DPRISM cohort, based on\neither FISH results at baseline or our final classification, leveraging FISH, scRNAseq and WGS.\n-Is it possible to look at the M-protein / involved FLC kinetics in patients with biochemical\nprogression?\nWe thank the reviewer for their suggestion. We have now included additional figures\n(Revised Manuscript, Figures 2D & 2E) in our revised manuscript, demonstrating continuous\nincrease in M-protein and involved:uninvolved Free Light Chain (FLC) ratio after confirmed\nbiochemical progression.\nFig 2E.\nFig 2D.\nRevised Figure 2. D) Line plot of serial M-spike levels in biochemical progressors (n=19), where time\nof biochemical progression (BPD) has been set at 0. Two biochemical progressors without measurable\nM-protein, one with light-chain disease and one with IgA disease, who were followed by FLCs or serum\nIgA levels respectively, were excluded from this visualization. E) Line plot of serial involved:uninvolved\nFLC ratio values in biochemical progressors (n=21), where time of biochemical progression (BPD) has\nbeen set at 0.\n- Please, state clearly which patients progressed on treatment vs. after 20 cycles. Among those\nwith progression after 20 cycles, which patients were early progressors within 0-6 or 0-12 months?\nI suggest to also update in Figure 1A (consort) the patients who discontinued the treatment due\nto PD (please also consult the CONSORT guidelines here).\nSix patients developed biochemical PD while on therapy and 15 patients developed\nbiochemical PD after completing therapy. Four of these were within 1 year after completing\ntherapy and the remaining progressed after one year of completion. The 2 patients that developed\nSLiM-CRAB progression developed it after therapy ended (one had BMPCs of 60% at end of\ntreatment bone marrow biopsy and the other progressed within 1 year based on FLC ratio of >\n100). There were no patients that discontinued therapy due to biochemical PD while on treatment.\nThis information is now reported in our Revised Manuscript, p. 4.\n- I would suggest to clarify in the caption of Table 1 how high-risk cytogenetics was defined.\nPlease, also define 2/20/20 4-factor HP; I think it refers to the continuous IMWG 2020 model?\nWe have now consistently used IMWG cytogenetic criteria throughout the manuscript and\nthe relevant sections in Figure 1 and Table 1 have been relabeled to reflect that. The notation\n“2/20/20 4-factor HP” corresponds to the IMWG’s high-precision risk score tool, as the reviewer\nsuggested – we have now clarified this in Revised Manuscript, Table 1.\n- Can you add information on how a pretreated LR SMM patient could receive treatment in a HR-\nSMM trial (maybe add the trial number).\nOne patient met inclusion criteria for clinical trial NCT04775550 based on 2/20/20 criteria.\n- Please, clarify in the results text that you refer to high risk according to IMWG 2020 model (Fig4\nA+B).\nThis has now been clarified both in the Results section and in the figures themselves.\nAdditionally, we have used the 2020 IMWG criteria for high-risk cytogenetics consistently\nthroughout the manuscript to avoid confusion.\n- The paragraph on the new definition of high-risk cytogenetics is not clear. What do you mean by\n“empirically based” here? Is there a reference? And where does the evidence come from to sum\nup scores based on the number of aberrations? In R2-ISS this is possible, but it does not include\ndel13q.\nWe thank the reviewer for their comment – at the request of our editor and reviewer #1,\nthis component of our analysis has been removed from the revised manuscript.\n- How was “tumor burden” defined? “Furthermore, no significant difference in tumor burden was\nobserved between progressors and non-progressors…”\nWe thank the reviewer for their question. This is clarified within parentheses in that same\nsentence – in this instance, tumor burden refers to the degree of bone marrow infiltration by\nplasma cells, as well as M-spike levels, as is standard in the field (Revised manuscript, p. 5).\nMethods:\n- Why was daratumumab given intravenously? (and not subcutaneously?)\nThis trial was designed when subcutaneous daratumumab was not yet approved. Hence,\nIV formulation was used.\n- Eligibility criteria and response assessment: IMWG response criteria rely on a stepwise\napproach of measurable disease (secretory, low secretory, etc.; see 2016 paper). Please add\ndetails on which patients had measurable or low secretory disease, etc., according to IMWG\ncriteria. Did this impact the actual depth of response in this study?\nAll patients enrolled in the study met the study inclusion criteria for high-risk MGUS and\nlow-risk SMM. Note that the measurable disease criteria were developed for the MM setting. In\nour study, 7/41 patients had M protein concentration < 0.5 g/dl, a threshold that has been\ncommonly used in other myeloma clinical trials for measurable disease. Of those, 5 had IgA\nisotype with either elevated IgA values or serum free light chains that were utilized to calculate\nresponse, and 2 patients had light chain disease with elevated serum free light chains that were\nused instead.\n- Please clarify if response rates are confirmed response according to IMWG 2016 criteria.\nThe response rates are reported per the 2016 IMWG response criteria. This information\nis also reported in the Methods section of the manuscript (Revised manuscript, p. 8).\n- Please clarify whether regular imaging PET-CT or MRI was part of the follow-up (and how\nfrequently).\nAdvanced imaging with PET/CT or a skeletal survey combined with whole-body MRI was\nperformed at screening and at end of treatment and was strongly recommended to be performed\nyearly during follow-up. Most patients continued to have advanced imaging during their follow-up\nperiod on this study.\n- The eligibility criteria are very condensed in the study protocol. Can you clarify that monoclonal\nprotein (in case of MGUS or SMM) or clonal plasma cells (in case of SMM) had to be present for\ninclusion in the trial.\nWe thank the reviewer for their request. The eligibility criteria included patients with high-\nrisk MGUS (2 out of 3 risk factors: Abnormal free light-chain (FLC) ratio (<0.26 or >1.65), M-\nprotein concentration (≥1.5 g/dL), Non-IgG M protein (including IgA)) and low-risk SMM (LR-SMM)\nwith only one of the following risk factors (Monoclonal Protein ≥ 3 g/dL, ≥ 10% Bone Marrow\nPlasma Cells, FLC ratio < 0.125 or > 8). Clonality was established for all patients. Specifically, out\nof 41 patients in the trial, 40 were positive for a monoclonal protein on immunofixation (IFX), while\nthe remaining patient, a patient with light-chain LR-SMM, had 20% infiltration with bone marrow\nplasma cells and a FLC ratio of 7.67.\n- The LR-SMM definition is debatable in my opinion. How is your LR-SMM definition justified\nempirically? As an example, a patient with M-protein 10 g/l, FLC ratio 7, BMPC 30% + deletion\n17p could have been included in your trial, though I (and you probably as well) would not consider\nthis LR.\nWe appreciate this comment from the reviewer, which highlights the discordance among\ncurrently utilized criteria for risk assessment in smoldering myeloma. Our trial used the definition\nof low-risk SMM per the Mayo 2008 criteria. This issue of risk stratification is also apparent in\nother ongoing and previously conducted trials in SMM, including high-risk SMM trials such as\nAQUILA, which also included patients with low and intermediate-risk SMM. A more uniform\ninclusion criteria may alleviate this concern for future studies. Additionally, following the example\nset with the 2025 IMS criteria for high-risk MM, it is critical for high-risk SMM criteria to also include\nkey genomic variables, such as Del17p, which was highlighted by the reviewer and which is not\nincluded in the 2020 IMWG criteria for high-risk SMM.\n- Can you please provide a data sharing statement for the clinical data as well.\nWe thank the reviewer for their request. We have now included a Supplemental Table\ncontaining outcome and toxicity data for all 41 patients in the trial (Revised Manuscript,\nSupplemental Table 1).\nDiscussion:\n- Lines 237ff: BM infiltration is highly variable across the skeleton; this spatial heterogeneity should\nbe mentioned here as well. As such, I am not sure if BMPC is a reliable surrogate of tumor burden.\nWe thank the reviewer for their comment. We agree that there are limitations to the use of\nbone marrow infiltration % as the sole surrogate of tumor burden, however it remains one of the\ngold standard approaches to estimating tumor burden in the field. Furthermore, we typically look\nat both BM infiltration and M-protein levels, which are measured in the blood and thus offer\nperhaps a more complete picture of disease burden across the body. In this instance, we did\ncompare both BM infiltration % and M-protein levels between biochemical progressors and non-\nprogressors in this sub-cohort and found no significant differences in either (Revised\nmanuscript, p. 5).\n“Furthermore, no significant difference in tumor burden was observed between progressors and\nnon-progressors (two-sided Wilcoxon rank-sum, p=0.644 and p=0.581 for BM infiltration and M-\nspike, respectively).”\nReviewer #3 (Remarks to the Author):\nThis is a small well performed single arm phase II study of daratumumab treatment for SMM. The\npoint is that daratumumab has recently been approved for SMM treatment and they attempt to\ndescribe its activity in LR SMM and HR MGUS. To aid in this utility they apply a novel score they\nhave developed. The study is interesting and well performed. The results may help in the clinical\nuse of daratumumab for myeloma precursor conditions.\nWe thank the reviewer for their kind comments. We kindly note that at the request of our\neditor and reviewers, we have now removed the novel score section from our revised manuscript.\nReviewer #4 (Remarks to the Author):\nThis manuscript presents the results of a well-conducted clinical study evaluating daratumumab\nin patients with high-risk MGUS and low-risk SMM, with a particular focus on early intervention\nand its potential to delay progression. The overall design is sound, the statistical methodology is\ngenerally appropriate, and the study provides valuable insights into this patient population. My\ncomments below focus mainly on statistical methodology and its reporting, as this is crucial for\nreproducibility and for allowing readers to properly interpret the study outcomes.\n1. For the evaluation of ORR, you used a two-sided 90% confidence interval. Please specify the\ntwo-sided significance level used in the power calculation for the statistical method. If it exceeds\n5%, please explain the reason for this choice. Additionally, please justify why 95% confidence\nintervals were used for endpoints other than ORR, given that ORR is the primary efficacy\nendpoint.\nWe thank the reviewer for their comment. Two considerations motivated our choice of\nusing a 90% confidence interval for the primary endpoint in power calculations:\ni) Hypothesis testing with a significance threshold of > 31 positive outcomes (as specified\nin our protocol) corresponds to a one-sided type I error rate of 0.032 (or 0.064 if interpreted as a\ntwo-sided test).\nii) Likewise, using a more stringent significance threshold of > 32 positive outcomes results\nin a one-sided type I error rate of 0.016 (or 0.032 for a two-sided interpretation).\nWe selected the threshold of > 31 positive outcomes because the corresponding type I\nerror rate is the closest to the commonly used target of 0.025. Since the resulting type I error\nexceeds 0.025, the corresponding hypothesis test is not an α = 5% test but an α =10% test. This\nexplains our use of a 90% confidence interval in the study protocol and our original reporting of\nORR results. Of note, as discussed in the Methods section, enrollment was ended early due to\nthe COVID-19 pandemic, with a cohort of 41 patients, instead of our originally planned number of\n50 (Revised manuscript, p. 8).\nTo address the reviewer’s concern, we decided to report the more stringent 95%\nconfidence intervals instead for all endpoints to ensure consistence across the manuscript, but\nadditionally reported 90% confidence intervals for ORR and deep response rate to align with the\nstudy protocol (for ORR results, please see Revised manuscript, p. 4).\n2. In Figure 5, although the statistical methods section does not mention it, you appear to have\napplied a Benjamini–Hochberg procedure for multiple-comparison adjustment. Please, clarify for\nwhich specific set of multiple tests this correction was applied, and explicitly state the significance\nlevel used after adjustment.\nWe thank the reviewer for their comment. The use of Benjamini-Hochberg for multiple\nhypotheses testing correction is explicitly mentioned in our Methods section pertaining to single-\ncell RNA-seq analysis where it was used. Specifically, it was employed wherever multiple\nhypotheses were tested: (i) Figure 5B: all immune cell types (n=20) were tested for an association\nwith biochemical progression and CD56dim NK cells were the only population passing the\nsignificance threshold, which is set at 0.05 throughout analysis, as mentioned in the Methods\nsection; (ii) Figures 5E & 5F: genes that pass the criteria discussed in the Methods section (n=660\nin 5E and n=603 in 5F) were tested for differential expression and p-values were adjusted with\nthe Benjamini-Hochberg approach; genes with an adjusted p-value (q-value) of < 0.05 were\nlabeled, as described in the Figure legend.\n3. In Figure 5B, the notation “q” is used — is this intended to denote an adjusted p-value (i.e., q-\nvalue from FDR correction)? Please clarify.\nThis is correct, q-value refers to the BH-adjusted p-value. Specifically, we compared cell\ntype proportions between biochemical progressors and non-progressors for all 20 immune cell\npopulations, and corrected those p-values using the BH approach. Only CD56dim NK cells\npassed our alpha threshold of 0.05 and were thus visualized. This is explained in our Results\nsection (Revised manuscript, p. 5):\n“First, we compared the proportions of all immune cell types (n=20) between progressors (n=18)\nand non-progressors (n=16). Interestingly, biochemical progressors had significantly higher\nproportions of CD56dim NK cells at baseline compared to non-progressors (two-sided Wilcoxon\nrank-sum, q=0.0364) (Figure 5B).”\n4. The manuscript mentions 95% confidence intervals for the Kaplan–Meier curves. Please\nindicate clearly where these intervals were actually used in the analysis or figures, and revise the\nstatistical methods section to focus on the analyses that were actually performed in this study.\nWe thank the reviewer for their feedback; since we did not visualize 95% confidence\nintervals in our KM plots, we have removed the corresponding statement from the Methods\nsection of our revised manuscript."}, {"round": 2, "reviewer_comments": {"reviewer_1": "Overall, the authors have adequately responded to my comments. I have a few minor points to\nmake:\n1. Abstract: Please state clearly in the abstract that ORR was 54%, ≥VGPR rate was 17%, and\nthe fact that the study did not meet its primary endpoint (which was ≥VGPR rate of 50% as per\nthe methods).\n2. Globally: Throughout the manuscript, please change “deep responses” to ≥VGPR rate since “deep” is a vague term and\ninterpreted differently by different clinicians. Alternatively, define “deep responses” early in the paper.", "reviewer_2": "I would like to thank the authors for addressing my comments and concerns. The manuscript\nreports on a practice-informing clinical trial and I congratulate the group on this important work.", "reviewer_3": "The changes implemented significantly improve the manuscript", "reviewer_4": "There is no problem."}, "author_response": "RESPONSE TO REVIEWERS\nWe would like to once again thank our reviewers for their feedback, which we believe has\nimproved the quality of our manuscript.\nPlease, see below for a point-by-point response to reviewer comments:\nReviewer #1 (Remarks to the Author):\nOverall, the authors have adequately responded to my comments. I have a few minor points to\nmake:\n1. Abstract: Please state clearly in the abstract that ORR was 54%, ≥VGPR rate was 17%, and\nthe fact that the study did not meet its primary endpoint (which was ≥VGPR rate of 50% as per\nthe methods).\nWe thank the reviewer for their request. We have revised our abstract to include this information:\n“The rate of Very Good Partial Response or better is 17% (95% CI: 7-32), which is comparable to\nwhat was observed in HR-SMM and does not meet the study’s primary endpoint. The overall\nresponse rate is 54%, with two patients developing MM and 51% biochemical progression.”\n2. Globally: Throughout the manuscript, please change “deep responses” to ≥VGPR rate since\n“deep” is a vague term and interpreted differently by different clinicians. Alternatively, define\n“deep responses” early in the paper.\nWe have revised the final paragraph of our Introduction, where the trial is first introduced, as\nsuch: “In this study, we aimed to assess whether single-agent daratumumab could induce deep\nresponses (i.e., Very Good Partial Response (VGPR) or better) and improve long-term\noutcomes in patients with HR-MGUS and low-risk SMM (LR-SMM).”\nAdditionally, we have added an explanation of the term “deep response” in our Discussion\n(Revised Manuscript, p.7) and the Statistics & Reproducibility section of our Methods (Revised\nManuscript, p.8).\nReviewer #2 (Remarks to the Author):\nI would like to thank the authors for addressing my comments and concerns. The manuscript\nreports on a practice-informing clinical trial and I congratulate the group on this important work.\nWe thank the reviewer for their kind comment.\nReviewer #3 (Remarks to the Author):\nThe changes implemented significantly improve the manuscript\nWe thank the reviewer for their feedback in the prior round, which helped us improve the\nmanuscript.\nReviewer #4 (Remarks to the Author):\nThere is no problem.\nWe thank the reviewer."}]

Decision letter