Abstract

Clinical severity scores facilitate comparisons to understand risk factors for severe illness. For the 2022 multinational monkeypox clade IIb virus outbreak, we developed a 7-item Mpox Severity Scoring System (MPOX-SSS) with initial variables refined by data availability and parameter correlation. Application of MPOX-SSS to the first 200 patients diagnosed with mpox revealed higher scores in those treated with tecovirimat, presenting >3 days after symptom onset, and with CD4 counts <200 cells/mm3. For individuals evaluated repeatedly, serial scores were concordant with clinical observations. The pilot MPOX-SSS demonstrated good discrimination, distinguished change over time, and identified higher scores in expected groups.

Clinical severity scores help health care providers and researchers assess and compare patient illness in a standardized fashion. They can be particularly useful when seeking to identify risk factors for severe illness, monitor disease progression, or evaluate treatment efficacy in observational research and clinical trials. Ideal clinical scoring systems require the fewest variables possible and rely on readily available data, such as findings from relevant clinical examinations without requirement for laboratory data. Such tools can then be used prospectively and possibly retrospectively (if the required data are captured in clinical records) in both resource-limited and resource-intense settings. Historically, most mpox severity indicators focused on fever, abnormal laboratory values, or number of skin lesions [1, 2]. However, the 2022 mpox outbreak from the clade IIb virus has had several unique features—including 99% of cases occurring in men who have sex with men and higher rates of genital, rectal, and pharyngeal lesions—and while most patients continue to have skin lesions, they have been fewer in number, progressed asynchronously, and been seen with and without the classic viral prodrome [3]. In response to the emerging multinational 2022 clade IIb mpox virus outbreak, we sought to develop and validate an Mpox Severity Scoring System (MPOX-SSS).

METHODS

Score Design

We initiated the development of the MPOX-SSS with a comprehensive literature review to identify potential variables. A panel of experts employed consensus methods, which are useful for synthesizing information when there is no unanimous opinion due to insufficient or excessive information [4]. Specifically, we used a modified nominal group technique to streamline the list of potential variables and assign severity scores on a scale of 0 to 4 [5]. This resulted in unanimous agreement on potential variables and scale.

The proposed variables and scales were shared via email, and feedback was gathered through email and virtual meetings with the subject matter experts. Three rounds of feedback were conducted to develop an initial scoring instrument. The instrument was then refined with a set of deidentified data, with alterations based on expert input, data availability, and parameter correlation. Over 9 iterations, the initial set of variables was honed to create a parsimonious final set of 7 scoring elements: number of active lesions, anatomic extent of lesion involvement, presence of confluent lesions, presence of bacterial superinfection, extent of mucosal areas affected, level of care, and analgesia requirement (Supplementary Figure 1).

Study Setting and Population

To pilot the MPOX-SSS, we conducted a retrospective chart review at a single academic urban medical center in northern New York City. The study population included 200 patients with confirmed mpox infection diagnosed 6 June 2023 to 24 August 2023. Vaccination against mpox was available in New York City starting 22 June 2023. The patients’ medical records were retrospectively reviewed to collect data on the 7 variables included in the MPOX-SSS.

Calculating the Outcome Measure

The MPOX-SSS was calculated by summing the points for each of the 7 variables, resulting in a score range of 0 to 23.

Analysis

In the absence of a reference standard for severity of illness, we chose to test construct validity by assessing the association between our severity measure and other surrogate measures expected to correlate with severity of illness: prescription of tecovirimat, CD4 count <200 cells/mm3 for persons with HIV, and presentation to care after 3 days of illness. We chose prescription of tecovirimat because, at the time of the study, the expanded access investigational drug protocol prioritized treatment of individuals who had or were at risk of severe disease, therefore making tecovirimat a reasonable proxy for severity. We used the Wilcoxon rank sum test to compare the scores of different patient groups. We performed secondary analyses comparing scores by HIV status and CD4 count, again with the Wilcoxon rank sum test. Finally, for a subset of patients with serial visits, we calculated the severity score over time from illness onset to demonstrate expected change over time.

The study was reviewed and approved via expedited review by the Columbia University Irving Medical Center Institutional Review Board with a waiver of informed consent.

RESULTS

Among the first 200 patients presenting with mpox, MPOX-SSS scores could be calculated retrospectively for 172 (86%). Missing data that precluded scoring included lesion number (13%) and presence of confluent lesions (7%). The study population had a median age of 34 years, with 99% born male, 96% who were men who have sex with men, 38% Hispanic, 28% Black, 49% with HIV (15% with CD4 count <200 cells/mm3 and 26% with CD4 >200 and viral load >1000 copies/mL), 28% taking HIV preexposure prophylaxis, and 57% treated with tecovirimat (Supplementary Table 1).

Median MPOX-SSS scores were similar in patients with and without HIV (8 vs 9, P = .12; Figure 1C , Supplementary Table 2). Median scores were higher in patients treated with tecovirimat (10 vs 5, P < .001; Table 1, Figure 1B ) as well as patients with CD4 counts <200 cells/mm3 (10 vs 8, P = .073; Figure 1C , Supplementary Table 3) and patients presenting >3 days after symptom onset (9 vs 6, P = .007). Four patients were diagnosed with mpox >14 days after their first vaccination dose (range, 16–26 days), with severity scores ranging from 3 to 8.

Severity score distribution (A) in the cohort, (B) by treatment with tecovirimat, and (C) by HIV status and CD4 count. D, Severity score over time in a subset of patients.
Figure 1.

Severity score distribution (A) in the cohort, (B) by treatment with tecovirimat, and (C) by HIV status and CD4 count. D, Severity score over time in a subset of patients.

Table 1.

Mpox Severity Score Breakdown by Treatment With Tecovirimat

CharacteristicOverall (N = 200)Treated With Tecovirimat (n = 115)Not Treated With Tecovirimat (n = 85)P Valuea
HIV status.007
 Positive98 (49)47 (41)51 (60)
 Negative102 (51)68 (59)34 (40)
Lesion burden, No.b<.001
 1–984 (48)35 (30)49 (83)
 10–9986 (49)76 (66)10 (17)
 ≥1004 (2)4 (3)0 (0)
Lesion burden, extent of body involvement<.001
 00 (0)0 (0)0 (0)
 1–396 (48)30 (26)66 (78)
 4–654 (27)41 (35.7)13 (15)
 7–931 (15.5)26 (22.6)5 (6)
 10–1219 (9.5)18 (15.7)1 (1)
Confluent lesionsc22 (12)18 (16)4 (5.6).04
Bacterial superinfection68 (34)57 (50)11 (13)<.001
Mucosal areas affected<.001
 None65 (33)15 (13)51 (60)
 1122 (61)89 (77.4)33 (39)
 212 (6.0)11 (9.6)1 (1)
 ≥30 (0)0 (0)0 (0)
Disposition.005
 Outpatient179 (90)97 (84)82 (96)
 Inpatient, non-ICU related to mpox21 (10)18 (16)3 (4)
 Inpatient, ICU related to mpox0 (0)0 (0)0 (0)
 Death0 (0)0 (0)0 (0)
Pain, analgesia requirement<.001
 Outpatient, none65 (32)8 (7.0)57 (67)
 Outpatient, OTCs58 (29)51 (44)7 (8)
 Outpatient, prescribed63 (32)43 (37)20 (24)
 Inpatient, oral meds, hospitalized8 (4.0)7 (6.1)1 (1)
 Inpatient, IV meds, hospitalized6 (3.0)6 (5.2)0 (0)
Severity scored<.001
 Mean (SD)8.4 (3.3)9.9 (2.6)5.3 (2.1)
 Median8105
 IQR6.0–11.08.0–12.03.0–7.0
CharacteristicOverall (N = 200)Treated With Tecovirimat (n = 115)Not Treated With Tecovirimat (n = 85)P Valuea
HIV status.007
 Positive98 (49)47 (41)51 (60)
 Negative102 (51)68 (59)34 (40)
Lesion burden, No.b<.001
 1–984 (48)35 (30)49 (83)
 10–9986 (49)76 (66)10 (17)
 ≥1004 (2)4 (3)0 (0)
Lesion burden, extent of body involvement<.001
 00 (0)0 (0)0 (0)
 1–396 (48)30 (26)66 (78)
 4–654 (27)41 (35.7)13 (15)
 7–931 (15.5)26 (22.6)5 (6)
 10–1219 (9.5)18 (15.7)1 (1)
Confluent lesionsc22 (12)18 (16)4 (5.6).04
Bacterial superinfection68 (34)57 (50)11 (13)<.001
Mucosal areas affected<.001
 None65 (33)15 (13)51 (60)
 1122 (61)89 (77.4)33 (39)
 212 (6.0)11 (9.6)1 (1)
 ≥30 (0)0 (0)0 (0)
Disposition.005
 Outpatient179 (90)97 (84)82 (96)
 Inpatient, non-ICU related to mpox21 (10)18 (16)3 (4)
 Inpatient, ICU related to mpox0 (0)0 (0)0 (0)
 Death0 (0)0 (0)0 (0)
Pain, analgesia requirement<.001
 Outpatient, none65 (32)8 (7.0)57 (67)
 Outpatient, OTCs58 (29)51 (44)7 (8)
 Outpatient, prescribed63 (32)43 (37)20 (24)
 Inpatient, oral meds, hospitalized8 (4.0)7 (6.1)1 (1)
 Inpatient, IV meds, hospitalized6 (3.0)6 (5.2)0 (0)
Severity scored<.001
 Mean (SD)8.4 (3.3)9.9 (2.6)5.3 (2.1)
 Median8105
 IQR6.0–11.08.0–12.03.0–7.0

Data are presented as No. (%) unless noted otherwise.

Abbreviations: ICU, intensive care unit; IV, intravenous; OTC, over-the-counter.

aP values are based on Pearson chi-square, Fisher exact, or Wilcoxon rank sum test. All P values <.05.

bNot treated with tecovirimat with unknown lesion number: n = 26.

cNot treated with tecovirimat with unknown confluent lesions: n = 14.

dNot treated with tecovirimat whose score could not be calculated: n = 28.

Table 1.

Mpox Severity Score Breakdown by Treatment With Tecovirimat

CharacteristicOverall (N = 200)Treated With Tecovirimat (n = 115)Not Treated With Tecovirimat (n = 85)P Valuea
HIV status.007
 Positive98 (49)47 (41)51 (60)
 Negative102 (51)68 (59)34 (40)
Lesion burden, No.b<.001
 1–984 (48)35 (30)49 (83)
 10–9986 (49)76 (66)10 (17)
 ≥1004 (2)4 (3)0 (0)
Lesion burden, extent of body involvement<.001
 00 (0)0 (0)0 (0)
 1–396 (48)30 (26)66 (78)
 4–654 (27)41 (35.7)13 (15)
 7–931 (15.5)26 (22.6)5 (6)
 10–1219 (9.5)18 (15.7)1 (1)
Confluent lesionsc22 (12)18 (16)4 (5.6).04
Bacterial superinfection68 (34)57 (50)11 (13)<.001
Mucosal areas affected<.001
 None65 (33)15 (13)51 (60)
 1122 (61)89 (77.4)33 (39)
 212 (6.0)11 (9.6)1 (1)
 ≥30 (0)0 (0)0 (0)
Disposition.005
 Outpatient179 (90)97 (84)82 (96)
 Inpatient, non-ICU related to mpox21 (10)18 (16)3 (4)
 Inpatient, ICU related to mpox0 (0)0 (0)0 (0)
 Death0 (0)0 (0)0 (0)
Pain, analgesia requirement<.001
 Outpatient, none65 (32)8 (7.0)57 (67)
 Outpatient, OTCs58 (29)51 (44)7 (8)
 Outpatient, prescribed63 (32)43 (37)20 (24)
 Inpatient, oral meds, hospitalized8 (4.0)7 (6.1)1 (1)
 Inpatient, IV meds, hospitalized6 (3.0)6 (5.2)0 (0)
Severity scored<.001
 Mean (SD)8.4 (3.3)9.9 (2.6)5.3 (2.1)
 Median8105
 IQR6.0–11.08.0–12.03.0–7.0
CharacteristicOverall (N = 200)Treated With Tecovirimat (n = 115)Not Treated With Tecovirimat (n = 85)P Valuea
HIV status.007
 Positive98 (49)47 (41)51 (60)
 Negative102 (51)68 (59)34 (40)
Lesion burden, No.b<.001
 1–984 (48)35 (30)49 (83)
 10–9986 (49)76 (66)10 (17)
 ≥1004 (2)4 (3)0 (0)
Lesion burden, extent of body involvement<.001
 00 (0)0 (0)0 (0)
 1–396 (48)30 (26)66 (78)
 4–654 (27)41 (35.7)13 (15)
 7–931 (15.5)26 (22.6)5 (6)
 10–1219 (9.5)18 (15.7)1 (1)
Confluent lesionsc22 (12)18 (16)4 (5.6).04
Bacterial superinfection68 (34)57 (50)11 (13)<.001
Mucosal areas affected<.001
 None65 (33)15 (13)51 (60)
 1122 (61)89 (77.4)33 (39)
 212 (6.0)11 (9.6)1 (1)
 ≥30 (0)0 (0)0 (0)
Disposition.005
 Outpatient179 (90)97 (84)82 (96)
 Inpatient, non-ICU related to mpox21 (10)18 (16)3 (4)
 Inpatient, ICU related to mpox0 (0)0 (0)0 (0)
 Death0 (0)0 (0)0 (0)
Pain, analgesia requirement<.001
 Outpatient, none65 (32)8 (7.0)57 (67)
 Outpatient, OTCs58 (29)51 (44)7 (8)
 Outpatient, prescribed63 (32)43 (37)20 (24)
 Inpatient, oral meds, hospitalized8 (4.0)7 (6.1)1 (1)
 Inpatient, IV meds, hospitalized6 (3.0)6 (5.2)0 (0)
Severity scored<.001
 Mean (SD)8.4 (3.3)9.9 (2.6)5.3 (2.1)
 Median8105
 IQR6.0–11.08.0–12.03.0–7.0

Data are presented as No. (%) unless noted otherwise.

Abbreviations: ICU, intensive care unit; IV, intravenous; OTC, over-the-counter.

aP values are based on Pearson chi-square, Fisher exact, or Wilcoxon rank sum test. All P values <.05.

bNot treated with tecovirimat with unknown lesion number: n = 26.

cNot treated with tecovirimat with unknown confluent lesions: n = 14.

dNot treated with tecovirimat whose score could not be calculated: n = 28.

The MPOX-SSS demonstrated good discrimination, with scores ranging from 3 to 18 with a median of 8.4 (IQR, 6–11; Figure 1A ). A cutoff of 8 was initially chosen to maximize the Youden index in 2 of our 3 end points [6]. With a cutoff <8 or ≥8, the MPOX-SSS had a sensitivity of 81%, specificity of 86%, positive predictive value (PPV) of 92%, and negative predictive value (NPV) of 69% for persons receiving tecovirimat; a sensitivity of 67%, specificity of 46%, PPV of 21%, and NPV of 87% for persons with HIV having a CD4 count <200 cells/mm3; and a sensitivity of 66%, specificity of 73%, PPV of 94%, and NPV of 24% for persons presenting >3 days after symptom onset. A cutoff of 7 was also explored given improved sensitivity. With a cutoff <7 or ≥7, the MPOX-SSS had a sensitivity of 91%, specificity of 74%, PPV of 88%, and NPV of 81% for persons receiving tecovirimat; a sensitivity of 92%, specificity of 41%, PPV of 25%, and NPV of 96% for persons with HIV having a CD4 count <200 cells/mm3; and a sensitivity of 74%, specificity of 50%, PPV of 91%, and NPV of 23% for persons presenting >3 days after symptom onset.

In a subset of individuals with serial mpox visits, the MPOX-SSS detected changes in severity scores over time, showing increasing/worsening and decreasing/improving severity. When reviewed by 2 clinicians, these changes were concordant with the patients’ clinical course, suggesting that the scoring system reflected disease progression or improvement (Figure 1D ).

DISCUSSION

Our results suggest that the MPOX-SSS can be useful for assessing disease severity in clinical practice and research settings.

The pilot MPOX-SSS was successfully applied retrospectively to 86% of charts, which suggests that it is easy to use and can be employed for retrospective analyses, as it captures data routinely collected for most patients with mpox. The pilot MPOX-SSS showed good discrimination across the spectrum of illness severity with clade IIb mpox virus infection. The MPOXX-SSS had a useful sensitivity, specificity, PPV, and NPV across our 3 surrogate markers of severity. For example, most patients treated with tecovirimat had scores >8, while most untreated patients scored <8.

Median scores were similar in patients with and without HIV, which is consistent with prior data on outcomes in this same patient population [7]. While the sample size was small, median scores were notably higher in those with CD4 counts <200 cells/mm3, consistent with the severe disease manifestations in patients living with AIDS described during this outbreak [8].

The capacity of the MPOX-SSS to track an individual patient's condition over time could provide a standardized means to monitor clinical progress and potentially tailor treatment plans, improve patient outcomes, and enhance overall quality of care. The MPOX-SSS could also be useful as a clinical trials research tool to help quantitatively assess the effectiveness of tecovirimat, brincidofovir, and vaccinia immune globulin intravenous, for which robust human data are currently lacking.

The MPOX-SSS has been used beyond the present pilot study, and results further support construct validity. A review of mpox lesions in 9 patients from New York City treated with tecovirimat revealed a median MPOX-SSS score of 8 at initiation of treatment, with 8 of 9 patients scoring 3 at an average of 13 days later, consistent with clinical improvement [9]. Furthermore, a global case series showed a decrease in the MPOX-SSS score between the first and second infections at the time of presentation, with a median of 7 (IQR, 7–10) as compared with 6.5 (IQR, 4–7), due to fewer affected mucosal areas and decreased analgesia needs [10]. Additionally, an evaluation of infections occurring in vaccinated persons had lower median scores (median, 5; IQR, 4–70), driven by reduced analgesia requirements and limited bacterial superinfection [10].

A strength of this severity scoring system is its simplicity, its ability to be used retrospectively (eg, for chart abstraction), and its capacity to discriminate across a reasonably broad range of values. Important limitations include the fact that we evaluated the instrument at a single site, the evaluation was limited to retrospective data, and there was only a small number of female and previously vaccinated patients. Additionally, the MPOX-SSS was developed for the 2022 clade IIb mpox virus outbreak, and its utility for assessing severity of illness from infection with clade I or IIa strains is unknown.

In summary, we believe that the MPOX-SSS could be a useful tool for health care providers to monitor disease progression and response to treatment and for researchers to elucidate factors associated with severe illness and evaluate the effectiveness of therapeutic interventions. The scoring system's simplicity and ease of use make it suitable for diverse clinical settings, including resource-limited and well-resourced environments. Future research is needed to validate the MPOX-SSS in larger, diverse patient populations as well as in circumstances where illness is caused by infection with virus strains other than clade IIb.

Supplementary Data

Supplementary materials are available at The Journal of Infectious Diseases online (http://jid.oxfordjournals.org/). Supplementary materials consist of data provided by the author that are published to benefit the reader. The posted materials are not copyedited. The contents of all supplementary data are the sole responsibility of the authors. Questions or messages regarding errors should be addressed to the author.

Notes

Author contributions. J. Z., M. J. G., T. J. W., W. F., I. D., and J. T. B. served as subject matter experts and designed the Mpox Severity Scoring System. J. Z., J. M., C. D., S. G., and K. S. collected and reviewed patient data. S. H. and J. Z. conducted the statistical analysis. J. Z. and J. T. B. supervised the findings of this work. All authors discussed the results and contributed to and reviewed the final manuscript.

Data availability. Deidentified participant data may be made available from the corresponding author on reasonable request and through an institutional data-sharing agreement.

Disclaimer. The findings and conclusions in this report are those of the authors and do not necessarily represent the official position of the Centers for Disease Control and Prevention.

Financial support. This work was supported by the National Institutes of Health (5T32AI100852-10 to J. M.; National Institute of Allergy and Infectious Diseases K23AI150378 to J. Z.).

Supplement sponsorship. This article appears as part of the supplement “Mpox: Challenges and Opportunities Following the Global 2022 Outbreak,” sponsored by the Centers for Disease Control and Prevention (Atlanta, GA).

References

1

Pittman
 
PR
,
Martin
 
JW
,
Kingebeni
 
PM
, et al.   
Clinical characterization and placental pathology of mpox infection in hospitalized patients in the Democratic Republic of the Congo
.
PLoS Negl Trop Dis
 
2023
;
17
:
e0010384
.

2

Huhn
 
GD
,
Bauer
 
AM
,
Yorita
 
K
, et al.   
Clinical characteristics of human monkeypox, and risk factors for severe disease
.
Clin Infect Dis
 
2005
;
41
:
1742
51
.

3

Thornhill
 
JP
,
Barkati
 
S
,
Walmsley
 
S
, et al.   
Monkeypox virus infection in humans across 16 countries—April-June 2022
.
N Engl J Med
 
2022
;
387
:
679
91
.

4

Jones
 
J
,
Hunter
 
D
.
Consensus methods for medical and health services research
.
BMJ Br Med J
 
1995
;
311
:
376
.

5

Van de Ven
 
AH
,
Delbecq
 
AL
.
The nominal group as a research instrument for exploratory health studies
.
Am J Public Health
 
1972
;
62
:
337
.

6

Perkins
 
NJ
,
Schisterman
 
EF
.
The Youden index and the optimal cut-point corrected for measurement error
.
Biom J
 
2005
;
47
:
428
41
.

7

McLean
 
J
,
Stoeckle
 
K
,
Huang
 
S
, et al.   
Tecovirimat treatment of people with HIV during the 2022 mpox outbreak: a retrospective cohort study
.
Ann Intern Med
 
2023
;
176
:
642
8
.

8

Mitjà
 
O
,
Alemany
 
A
,
Marks
 
M
, et al.   
Mpox in people with advanced HIV infection: a global case series
.
Lancet
 
2023
;
401
:
939
49
.

9

Seifu
 
L
,
Garcia
 
E
,
McPherson
 
TD
, et al.   
Notes from the field: posttreatment lesions after tecovirimat treatment for Mpox—New York City, August-September 2022
.
MMWR Morb Mortal Wkly Rep
 
2023
;
72
:
471
2
.

10

Hazra
 
A
,
Zucker
 
J
,
Bell
 
E
, et al.   
Mpox in people with past infection or a complete vaccination course: a global case series
.
Lancet Infect Dis.
Published online 4 September
2023
. doi:

Author notes

Potential conflicts of interest. J. Z., W. F., T. J. W. are part of the NIH funded study of tecovirimat for mpox (STOMP) leadership team.

All authors have submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest.

This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/pages/standard-publication-reuse-rights)

Supplementary data