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RESEARCH ARTICLE
Effectiveness of nirmatrelvir-ritonavir for the
treatment of patients with mild to moderate
COVID-19 and at high risk of hospitalization:
Systematic review and meta-analyses of
observational studies
Kathiaja Miranda SouzaID
1☯
, Gabriela Carrasco
2☯
*, Robin Rojas-Corte
´s
3‡
, Mariana Michel
Barbosa
4☯
, Eduardo Henrique Ferreira BambirraID
4‡
, Jose
´Luis Castro
5‡
, Juliana Alvares-
Teodoro
4,6‡
1Independent Consultant, Belo Horizonte, Brazil, 2Red Argentina Pu
´blica de Evaluacio
´n de Tecnologı
´as
Sanitarias (REDARETS), Neuque
´n, Argentina, 3Department of Health Systems and Services, Pan American
Health Organization, Unit of Medicines and Health Technologies, Washington, DC, United States of America,
4Postgraduate Program in Medicines and Pharmaceutical Services, Federal University of Minas Gerais,
Belo Horizonte, Minas Gerais, Brazil, 5Fundacio
´n Para la Innovacio
´n, la Formacio
´n, la Investigacio
´n y el
Desarrollo Comunita
´rio (FU
¨NDEC), San Isidro, S/C de Tenerife, España, 6Faculty of Pharmacy, Department
of Social Pharmacy, Federal University of Minas Gerais, Belo Horizonte, Minas Gerais, Brazil
☯These authors contributed equally to this work.
‡ These authors also contributed equally to this work
*gabi_carrasco@hotmail.com
Abstract
Objective
To assess the effectiveness of nirmatrelvir-ritonavir in the treatment of outpatients with mild
to moderate COVID-19 who are at higher risk of developing severe illness, through a sys-
tematic review with meta-analyses of observational studies.
Methods
A systematic search was performed, in accordance with the Cochrane search methods, to
identify observational studies that met the inclusion criteria. The outcomes of mortality and
hospitalization were analyzed. Search was conducted on PubMed, EMBASE, and The
Cochrane Library. Two reviewers independently screened references, selected the studies,
extracted the data, assessed the risk of bias using ROBINS-I tool and evaluated the quality
of evidence using the GRADE tool. This study followed the PRISMA reporting guideline.
Results
A total of 16 observational studies were finally included. The results of the meta-analysis
showed that in comparison to standard treatment without antivirals, nirmatrelvir-ritonavir
reduced the risk of death by 59% (OR = 0.41; 95% CI: 0.35–0.52; moderate certainty of evi-
dence). In addition, a 53% reduction in the risk of hospital admission was observed (OR =
PLOS ONE
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OPEN ACCESS
Citation: Souza KM, Carrasco G, Rojas-Corte
´s R,
Michel Barbosa M, Bambirra EHF, Castro JL, et al.
(2023) Effectiveness of nirmatrelvir-ritonavir for
the treatment of patients with mild to moderate
COVID-19 and at high risk of hospitalization:
Systematic review and meta-analyses of
observational studies. PLoS ONE 18(10):
e0284006. https://doi.org/10.1371/journal.
pone.0284006
Editor: Yoon-Seok Chung, Korea Disease Control
and Prevention Agency, REPUBLIC OF KOREA
Received: March 21, 2023
Accepted: September 13, 2023
Published: October 12, 2023
Copyright: ©2023 Souza et al. This is an open
access article distributed under the terms of the
Creative Commons Attribution License, which
permits unrestricted use, distribution, and
reproduction in any medium, provided the original
author and source are credited.
Data Availability Statement: All relevant data are
within the manuscript and its Supporting
information files.
Funding: This study was funded by the grant
‘Working together to fight antimicrobial resistance’,
internal number 049126, EUC agreement PI/2019/
406-773; as well as by the partnership between the
Government of Canada and the Pan American
0.47; 95% CI: 0.36–0.60, with very low certainty of evidence). For the composite outcome of
hospitalization and/or mortality, there was a 56% risk reduction (OR = 0.44; 95% CI: 0.31–
0.64, moderate certainty of evidence).
Conclusion
The results suggest that nirmatrelvir-ritonavir could be effective in reducing mortality and
hospitalization. The results were valid in vaccinated or unvaccinated high-risk individuals
with COVID-19. Data from ongoing and future trials may further advance our understanding
of the effectiveness and safety of nirmatrelvir-ritonavir and help improve treatment guide-
lines for COVID-19.
Introduction
Declared a pandemic by the World Health Organization (WHO) in March 2020, COVID-19
(coronavirus disease) has posed a significant challenge to healthcare professionals, managers,
and health systems, due to its rapid spread, lack of treatment, severity, and unpredictable
nature. As of March 7, 2023, there were 759,408,703 confirmed cases of COVID-19, including
6,866,434 deaths [1].
WHO data indicates that about 15% of mild/moderate cases progress to severe disease
requiring hospitalization and respiratory support, and 5% of patients develop the critical form
requiring admission to the Intensive Care Unit (ICU). The high number of cases has resulted
in a massive and sudden influx of patients to emergency services, leading to large number of
hospitalizations, requiring isolation, oxygen support, intubation, and invasive mechanical ven-
tilation [2].
In Latin America, the COVID-19 pandemic has affected countries differently. Among some
of these countries, the reported incidence rate ranged from 4.59% in Jamaica to 25.6% in
Chile. In contrast, Peru had the highest case fatality rate (5.1%) and Chile the lowest case fatal-
ity rate (1.3%) among the countries analyzed [3].
In December 2020, the first dose of the COVID-19 vaccine was administered, and since
then, 13.01 billion doses have been given worldwide, corresponding to 68.5% of the world’s
population receiving at least one dose of the vaccine. In Latin America, the proportions of vac-
cinated individuals vary significantly between countries. While in Jamaica 28.2% of people
received at least one dose, and 24.8% received the second dose, in Chile, more than 90% of the
population received two doses of the COVID-19 vaccine [1].
In the context of the appearance of new variants and, in some countries, low vaccination
rates, either due to unavailability or lack of adherence, the existence of medicines capable of
controlling symptoms and avoiding hospitalizations and deaths is becoming increasingly
under focus. In April 2022, the WHO published a new update of the “Guideline Therapeutics
and COVID-19: living guideline”. In this publication, WHO made a strong recommendation
in favor of nirmatrelvir-ritonavir, for patients with mild and moderate COVID-19 at high-risk
of hospital admission, qualifying it as the best therapeutic option for those patients, such as
unvaccinated, elderly or immunocompromised patients. The guideline development group
concluded that nirmatrelvir-ritonavir represents a superior option as it may be more effective
in preventing hospitalization than the alternatives compared (standard treatment, molnupira-
vir and remdesivir), though with important pharmacokinetic interactions, it apparently has
fewer concerns than monulpiravir regarding adverse effects, and it is easier to administer than
intravenous remdesivir and monoclonal antibodies [4]. The Ongoing Living Systematic
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Health Organization (PAHO/WHO). The funders had
no role in study design, data collection and
analysis, decision to publish, or preparation of the
manuscript.
Competing interests: The authors have declared
that no competing interests exist. Authors hold
sole responsibility for the views expressed in the
manuscript, which may not necessarily reflect the
opinion or policy of the Pan American Health
Organization. This does not alter our adherence to
PLOS ONE policies on sharing data and materials.
Review published by Pan American Health Organization (PAHO) presented the same direc-
tion of the recommendations [5]. The Systematic Review and meta-analysis conducted by
Cheema et al (2023) also concluded that, in general, nirmatrelvir-ritonavir is effective and safe
in the treatment of COVID-19 patients [6].
It is noteworthy that randomized clinical trials (RCT) investigating the use of nirmatrelvir-
ritonavir in the context of current COVID-19 variants, such as the Omicron variant, for non-
hospitalized symptomatic COVID-19 patients with a full COVID-19 vaccination schedule
and/or who are at risk of progressing to severe disease have not yet been published. However,
there is one ongoing RCT, namely PANORAMIC trial (ISRCTN30448031), that is currently
investigating the use of nirmatrelvir-ritonavir. The results of this trial is highly anticipated. On
the other hand, EPIC-SR study (NCT05011513) has been terminated due to a very low rate of
hospitalization or death observed in the standard-risk patient population. Although random-
ized clinical trials (RCTs) provide the most reliable data on efficacy and safety due to their
high level of control, it may not be appropriate to extrapolate their results to the general popu-
lation at this stage. Therefore, it is necessary to include observational studies to obtain a more
comprehensive understanding of the real-world use and effects of nirmatrelvir-ritonavir
[5,7,8].
Nirmatrelvir-ritonavir is a high-cost medicine, the target population is quite large, and in
several countries the medicine has yet to be approved for emergency use, marketing or reim-
bursement into the health system due to the uncertainties and challenges related to its effec-
tiveness, further information on safety, high risk (e.g., vaccination status), cost, and resource
requirements for administration.
In order to support the pharmacotherapeutic committees, health technology assessment
agencies, and other decision-making bodies for the management of patients diagnosed with
COVID-19 and eligible for nirmatrelvir-ritonavir treatment, a systematic review was con-
ducted to assess the effectiveness of nirmatrelvir-ritonavir. The objective of this study was to
evaluate the performance of nirmatrelvir-ritonavir in a real-world setting.
Materials and methods
Search strategy
Two independent investigators conducted a thorough literature search on PubMed, EMBASE,
and The Cochrane Library. Validated filters for observational studies were applied to each
database to ensure relevant results. In addition, searches were conducted on Epistemonikos
and ClinicalTrials to identify possible systematic reviews and primary studies not retrieved in
the main databases. The search strategies developed for each platform are detailed in the Sup-
porting Information (Table 1 in S1 File) and were executed until January 4, 2023. The records
obtained from the databases were imported into Mendeley
1
for the identification and elimi-
nation of duplicate studies. The report was based on the Preferred Reporting Items for System-
atic Reviews and Meta-analysis (PRISMA) (Table 2 in S1 File). This study didn´t need the
approval of an ethics committee since it is a secondary study [9]. This review was not regis-
tered in PROSPERO.
Study selection
After exporting a single Mendeley
1
file, the records were imported into Rayyan [10]. Two
independent researchers selected the records, and a third evaluator was consulted in case of
doubts, both for screening (reading titles and abstracts) and eligibility (reading full texts).
The inclusion criteria for this systematic review were: (1) population: outpatients with
COVID-19 who are at high risk of developing severe disease; (2) intervention: nirmatrelvir/
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ritonavir; (3) comparator: standard treatment or no antiviral treatment; (4) death and/or hos-
pitalization (5) type of study: observational studies. No restrictions were imposed on publica-
tion date, language, or follow-up time. Studies reported only in conference proceedings were
excluded.
The exclusion criteria were: (a) the study was a review article, letters to the editor, com-
ments, consensus documents, clinical trials, pre-clinical studies, animal studies, or case
reports; (b) the study did not focus on patients with COVID-19 or the diagnosis was unclear.
Data extraction and quality assessment
Two independent researchers performed data extraction using a standardized collection
method with Microsoft Office Excel
1
. A third review author fully checked all extracted data.
The following information regarding the demographic characteristics of the studies was col-
lected: first author, publication year, country, study design, general characteristics of the popu-
lation, time of follow-up, predominant variant of SARS-CoV-2 at the time of the study,
diagnostic criteria, number of participants per alternative compared, average age, proportion
of male population, proportion of white population, comorbidities, body mass index (BMI),
and COVID-19 vaccination status. Additionally, for dichotomous outcomes, data were col-
lected on the number of patients with events in each compared alternative, odds ratio (OR),
hazard ratio (HR), relative risk (RR), confidence interval (CI), or p-value.
The risk of bias was independently investigated by two researchers using the ROBINS-I
tool, which assesses the risk of bias for non-randomized studies [11]. Any discrepancies were
resolved by consensus. To evaluate publication bias for the primary outcomes, visual inspec-
tion of the funnel plot was employed. The quality of evidence was assessed using the GRADE
(Grading of Recommendations Assessment, Development and Evaluation) tool [12].
Data synthesis and sensitivity analysis
The primary outcomes were hospitalization, mortality and the composite outcome of mortality
and/or hospitalization within 35 days. Further subgroup analyses were conducted based on
vaccination status and age group. To analyze the data, we used Review Manager
1
(RevMan)
Version 5.4.1 (Review Manager, The Nordic Cochrane Centre, The Cochrane Collaboration,
Copenhagen, Denmark). The heterogeneity of the results was assessed using the Cochran’s Q
test and I
2
-statistic. If the p-value was less than .05 in the Q-statistic and I
2
was 50%, the het-
erogeneity was considered significant. We used the Mantel-Haenszel statistical method, the
Sidik-Jonkman estimator for tau2, and the Hartung-Knapp adjustment for the random effects
model to calculate pooled odd ratios (ORs) with corresponding 95% confidence intervals (CI).
When numerical data were unavailable, we used the PlotDigitizer v3. 2022 free version to
extract data from graphs. A sensitivity analysis was conducted to compare the published and
preprint studies, as well as those with and without techniques to adjust for patient characteris-
tics (either through propensity score matching (PSM) or inverse probability treatment weight-
ing (IPTW)).
To perform the meta-analyses, we assessed the homogeneity and transitivity by comparing
the PICO abbreviations of each study (population inclusion and exclusion criteria, definitions
of subpopulations, intervention and controls, and definitions of outcomes). As important dis-
crepancies were identified, we discussed them as possible limitations of the meta-analyses.
We presented the characteristics of the studies, the characteristics of the participants, the
individual results, and the methodological quality assessment of the included studies in a nar-
rative and descriptive statistical form (absolute and relative frequency, mean and SD or
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median and interquartile range [IQR]), including tables to assist in the presentation of results.
The narrative results were grouped by outcome, highlighting the alternatives compared.
Results
Search results and study selection
From the search strategy used, 182 publications were retrieved, with 162 citations remaining
after identifying and eliminating duplicates. All records were subjected to a peer review pro-
cess, and the full text of 32 potentially eligible articles was carefully considered. Of these 32
studies, 16 original articles were either not observational studies or did not have comparison
groups. Therefore, records pertaining to sixteen [16] observational studies were included in
the analysis. Fig 1 demonstrates the flow of our studies’ selection.
Study characteristics
The sixteen studies finally considered were conducted in 5 countries (Canada, China, United
States, Israel, and United Kingdom). Of these, as of the last update of the search, 12 studies
were published [13–24] and 4 were preprint studies [25–28]. All studies were retrospective
cohorts of data obtained from electronic records of hospitals and other healthcare centers, col-
lected from January 2021 to October 2022.
For the meta-analysis, fourteen studies were considered. Data from the studies by Wai
et al., 2022 (n = 27,872) and Lewnard et al., 2023 (n = 133,426) were not included in the meta-
analysis. The study by Wai et al. did not provide all the necessary data required for the pro-
posed meta-analysis, and there may be participant overlap between the study conducted by
Wai et al. and the study conducted by Wong et al. On the other hand, the study by Lewnard
et al. introduced a potential critical bias, as the evaluated cohort was a sample analysis where
one or more baseline characteristics were retained in the evaluation, rather than all relevant
baseline characteristics for an effectiveness assessment that make the groups minimally com-
parable. As a result, the cohort was still completely unbalanced [17,20,28].
All patients evaluated in the included studies, eligible for treatment with nirmatrelvir-rito-
navir, met the high-risk criteria for progression to severe COVID-19 defined by their
Fig 1. PRISMA flow chart of literature screening.
https://doi.org/10.1371/journal.pone.0284006.g001
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respective countries, which included criteria such as age, vaccination status, and presence of
comorbidities. In the study by Aggarwal et al., 2023, the decision to seek antiviral treatment
was made by patients and physicians, without necessarily meeting the eligibility criteria
defined by the United States government [24].
Regarding the initiation of treatment with nirmatrelvir-ritonavir, 8 studies were strict with
the initiation of treatment within the fifth day of symptom onset or positive COVID-19 test
[13,14,19–22,26,27]. In the other 6 studies, there was greater flexibility, as patients started treat-
ment with nirmatrelvir-ritonavir within 10 days of symptom onset or positive test [17,18,23–
25,28]. This was not mentioned in the other two meta-analyzed studies.
When assessing the reported vaccine types in the studies, it was found that only five studies
provided information on the specific vaccine types administered to the study population.
Among these studies, two reported the utilization of viral vector vaccines or mRNA vaccines
[15,18], while two studies exclusively reported the administration of mRNA vaccines [21,23].
Furthermore, one study indicated that the population received both inactivated virus vaccines
and mRNA vaccines [20]. However, the remaining studies did not provide explicit informa-
tion regarding the vaccines received by the study population. Nevertheless, considering the
countries where the studies were conducted, it is presumed that the majority of the population
received mRNA vaccines.
In total, data from 1,482,923 patients from 14 studies were included in the meta-analysis.
The characteristics of the included studies are shown in Tables 1and 2.
Risk of bias
The included studies were evaluated using the ROBINS-I tool, which assesses the risk of bias
in non-randomized studies. The supporting information provides further details on the risk of
bias assessments for studies that reported data on mortality, hospitalization, and the composite
outcome of hospitalization or mortality. Regarding the mortality outcome, 4 of the 13 included
studies had a low risk of bias, while 7 had a moderate risk. However, for the outcome of hospi-
talization within 35 days, 9 of the 11 studies were at risk of serious or critical bias, primarily
due to outcome measurement bias (Table 3 in S1 File). There was low risk of bias due to miss-
ing results or reporting bias.
Effectiveness outcomes
Table 3 shows the effect measures reported by the studies included in this review, stratified by
subgroup. In the supplementary material (Table 4 in S1 File), we report the aggregated results
reported and used in the meta-analysis. The following are the results of the meta-analyses con-
ducted by the evaluated outcome.
Mortality. Twelve studies reported mortality data, including 1,131,595 patients and 7,068
deaths [13,15,16,18–21,23–27]. In comparison to standard treatment without antivirals, nir-
matrelvir-ritonavir reduced the risk of death by 59% (OR = 0.41; 95% CI: 0.35–0.52; moderate
certainty of evidence) (Fig 2).
Three studies reported subgroup data by vaccination status [13,16,20] and four other stud-
ies reported data by age group [16,20,21,26]. In the analysis by vaccination status, nirmatrel-
vir-ritonavir reduced the risk of mortality both in the unvaccinated group (OR = 0.41; 95% CI:
0.29–0.58) and in the vaccinated group (OR = 0.31; 95% CI: 0.14–0.68), with no significant dif-
ference between the groups (Fig 3).
In the subgroup of patients under 60 years of age, there appears to be no difference between
treatment with nirmatrelvir-ritonavir compared to standard treatment (OR = 0.48; 95% CI:
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Table 1. Characteristics of included studies.
Study Study design Characteristics of included patients. Country Study period Time of
follow-
up
Predominant
SARS-CoV-
variants.
Funding
Ganatra
et al., 2022
[13]
retrospective
cohort
Adults aged 18 or older who were
vaccinated and subsequently contracted
COVID-19 at least 1 month after
vaccination and were not hospitalized.
United
States
1 December
2021 to 18
April 2022
30 days Not reported Not reported
Yip et al.,
2022 [14]
retrospective
cohort
Outpatient patients, regardless of
vaccination status, who attended one of
the selected clinics
China 16 February
2022 to 31
March 2022
30 days Omicron None declared
Wai et al.,
2023 [17]
retrospective
cohort
Hospitalized and non-hospitalized
patients aged 60 years or older or with
at least one chronic disease with mild to
moderate COVID-19.
China 22 February
2022 to 15
April 2022
30 days Omicron The Tung’s Foundation,
Innovation and Technology
Comission of Hong Kong
Hedvat et al.,
2022 [18]
retrospective
cohort
Non-hospitalized adult solid organ
transplant recipients with
asymptomatic, mild, or moderate
COVID-19.
United
States
16 December
2021 to 19
January 2022
30 days Omicron (BA.1) Not reported
Dryden-
Peterson
et al., 2022
[19]
retrospective
cohort
Outpatient patients aged 50 years or
older with COVID-19.
United
States
1 January 2022
to 17 July 2022
to
14 days
28 days
Omicron (BA.1.1,
BA.2, BA.2.12.1 y
BA.5)
U.S. National Institutes of
Health.
Wong et al.,
2022 [20]
retrospective
cohort
Outpatient patients with mild clinical
presentation of COVID-19 and high
risk of disease severity.
China 26 February
2022 to 26
June 2022
28 days Omicron (BA.2.2) Health and Medical Research
Fund
Arbel et. al,
2022 [21]
retrospective
cohort
Outpatient patients aged 40 years or
older with mild clinical presentation of
COVID-19 and high risk of disease
severity.
Israel 9 January 2022
to 31 March
2022
35 days Omicron None declared
Schwartz et.
al., 2023 [16]
retrospective
cohort
Outpatient patients aged 18 years or
older with COVID-19.
Canada 4 April 2022 to
31 August
2022.
30 days Omicron Ontario Ministry of Health
(MOH); the Ministry of Long-
Term Care (MLTC); Public
Health Ontario
Aggarwal
et al., 2023
[24]
retrospective
cohort
All non-hospitalized patients within the
Colorado healthcare system with a
positive test result for SARS-CoV-2.
United
States
26 March 2022
to 25 August
2022
28 days Omicron (BA.2/
BA2.12.1)
U.S. National Institutes of
Health
Najjar-
Debbiny
et al., 2022
[22]
retrospective
cohort
Patients 18 years old with COVID-19
who are not hospitalized and have at
least one comorbidity or condition
associated with high risk of severe
COVID-19.
Israel 1 January 2022
to 28 February
2022
28 days Omicron (BA.1) Not reported
Qian et al.,
2022 [15]
retrospective
cohort
Patients 18 years old with COVID-19
and a diagnosis of systemic
autoimmune rheumatic disease.
United
States
23 January
2022 to 30 May
2022
30 days Omicron Rheumatology Research
Foundation
Shah et al.,
2022 [23]
retrospective
cohort
Patients aged 18 years with COVID-
19 who are not hospitalized and have at
least 1 comorbidity or condition
associated with a high risk of severe
COVID-19.
United
States
1 April 2022 to
31 August
2022
30 days Omicron Not reported
Bajema et. al.,
2022 [25]*
retrospective
cohort
Non-hospitalized veteran patients with
at least one risk factor, clinical
presentation of COVID-19, and high
risk of disease severity.
United
States
1 January 2022
to 28 February
2022
30 days
31–180
days
Omicron
(B.1.1.529 y
BA1.1)
Veterans Health
Administration Health Services
Research & Development
(HSR&D)
Lewnard et.
al., 2023 [28]
*
retrospective
cohort
Outpatient patients aged 12 years and
older with COVID-19 within Kaiser
Permanente, Southern California
healthcare system.
United
States
8 April 2022 to
7 October 2022
30 days
60 days
Omicron (BA.2;
BA.4 y BA.5)
US Centers for Disease Control
& Prevention
National Institute for Allergy
and Infectious Diseases of the
US National Institutes of
Health.
(Continued )
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0.09–2.50), while treating patients over 60 years of age with nirmatrelvir-ritonavir suggests
greater protection against the risk of death (OR = 0.47; 95% CI: 0.40–0.55) (Fig 4).
It should be noted that the subgroup meta-analysis could only be performed among those
studies that reported data that could be grouped. Table 3 presents the results of the effect mea-
sures from other studies that reported the evaluation of these subgroups.
Furthermore, the sensitivity analysis did not reveal significant changes in the mortality rate
of published studies (OR = 0.42; 95% CI: 0.35–0.50) and preprint studies (OR = 0.23; 95% CI:
0.13–0.42). There were also no significant differences between matched studies (OR = 0.34;
95% CI: 0.25–0.47) and unmatched studies (OR = 0.38; 95% CI: 0.27–0.54) (Figs 1 and 2 in S1
File).
Hospitalization. Eleven studies reported data on hospitalization within 35 days of follow-
up after the initiation of the treatment, which included 963,626 patients, with the occurrence
of 11,903 events [13–15,19–21,23–27]
Compared to standard treatment or no antiviral treatment, the use of nirmatrelvir-ritonavir
resulted in a 53% reduction in the risk of hospital admission (OR = 0.47; 95% CI: 0.37–0.60,
with very low certainty of evidence) (Fig 5).
Four studies reported subgroups data by vaccination status [13,20,24,27] and five studies
reported age subgroups data [20,21,24,26,27]. In the subgroup analysis of state vaccination,
nirmatrelvir-ritonavir reduced the risk of hospitalization in both groups, non-vaccinated
(OR = 0.41; 95%CI: 0.16–1.05) and vaccinated (OR = 0.45; 95%CI: 0.25–0.81). It is worth not-
ing that when using the random effects method, the meta-analysis result introduced greater
inaccuracy in the data. Although each study showed a reduction in risk favoring the treatment
of nirmatrelvir-ritonavir in the non-vaccinated group, the effect magnitude was very different
between the studies in this analysis. In the subgroup analysis by age, nirmatrelvir-ritonavir
reduced the risk of hospitalization in both the group of individuals under 60 years (OR = 0.45;
95%CI: 0.25–0.82) and the group of individuals over 60 years (OR = 0.30; CI95%: 0.13–0.70),
without a significant difference between the two groups (Figs 6and 7).
The sensitivity analysis revealed significant changes in the hospitalization rate between pub-
lished studies (OR = 0.57; 95%CI: 0.46–0.71) and preprint studies (OR = 0.29; 95%CI: 0.10–
0.84). There were also differences between adjusted studies (OR = 0.52; 95%CI: 0.37–0.73) and
not adjusted (OR = 0.29; 95%CI: 0.15–0.56) (Figs 3 and 4 in S1 File).
Outcome composed of mortality and/or hospitalization. Five studies reported effective-
ness data based on the outcome composed of mortality and/ or hospitalization within 35 days
of follow-up after the start of treatment, which included 225,452 patients, with the occurrence
of 7,019 events [15,16,18,19,25]
Table 1. (Continued)
Study Study design Characteristics of included patients. Country Study period Time of
follow-
up
Predominant
SARS-CoV-
variants.
Funding
Zhou et. al.,
2022 [29]*
retrospective
cohort
Outpatient patients aged 12 years and
older with COVID-19 within Optum
repository, with >700 hospitals and
7000 clinics from all states in the US.
United
States
22 december
2021 to 8 May
2022
15 days
30 days
Omicron Pfizer Inc.
Patel et al.,
2022 [26]*
retrospective
cohort
Outpatient patients, aged 12 years at
study initiation, and diagnosed with
COVID-19
England 1 december
2021 to 31 May
2022
28 days Omicron (BA.1,
BA.2 y BA.5)
GlaxoSmithKline
Pharmaceuticals Ltd.
*preprint study.
https://doi.org/10.1371/journal.pone.0284006.t001
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Table 2. Characterization of participants included in the studies, according to the evaluated alternative.
Study Compared
alternatives
Number of
participants
Mean age (SD). Male
n (%)
White
n (%)
Comorbidities *
n (%)
BMC 30
kg/m2
n (%)
Primary series of
COVID-19 vaccine and/
or boosters
n (%)
Ganatra et al.,
2022 [13]
a
Nirmatrelvir-
ritonavir for 5 days.
1,130 57.5 (16.3) 418 (37.0) 925 (81.9) >50% had at least 1
comorbidity.
237 (21) 1,130 (100)
Standard treatment 1,130 57.7 (16.3) 406 (35.9) 941 (83.3) >50% had at least 1
comorbidity.
208 (18) 1,130 (100)
Yip et al., 2022
[14]
a
Nirmatrelvir-
ritonavir for 5 days.
4,921 70.8 (12.1) 2,247
(45.7)
NR 1,970 (40) 24.0
(4.2)
b,d
42.6 (15.8)
e
No antiviral
treatment.
4,758 70.5 (12.2) 2,178
(45.8)
NR 1,907 (40) 24.5
(4.7)
b,d
42.8 (15.7)
e
Wai et al., 2023
[17]
Nirmatrelvir-
ritonavir for 5 days.
4,442 4,366 (98,3%)
c
2,016
(45.4)
NR
f
>10% had at least 1
comorbidity.
NR NR
No antiviral
treatment.
23,430 21,904 (93,5%)
c
11,078
(47.3)
NR
f
>50% had at least 1
comorbidity.
NR NR
Hedvat et al.,
2022 [18]
Nirmatrelvir-
ritonavir for 5 days.
28 57.6 (44.3–68.6) 11 (39.3) NR 28 (100) 25.3 (22.3–
30)
b
23 (82.1)
No antiviral
treatment.
75 53.3 (37.6–64.6) 32 (42.7) NR 75 (100) 27 (23.3–
29.5)
b
61 (81.3)
Dryden-Peterson
et al., 2022 [19]
a
Nirmatrelvir-
ritonavir for 5 days.
11,797 50–64 years–
6,388 (54%)
65 years—
5,408 (46%)
4,880 (41) 10,164
(86) 3: 6,727 (57)
4: 5,070 (43)
i
4,013 (34) 10, 752 (91)
No antiviral
treatment.
32,248 50–64 years—
17,881(55%)
65 years
14,367 (45%)
12,603
(39)
27,266
(85) 3: 18,464 (57)
4: 13,784 (43)i
10,661 (33) 29,158 (90)
Wong et al., 2022
[20]
a
Nirmatrelvir-
ritonavir for 5 days.
5,542 4,758 (85.9%)
c
2,566
(46.3)
NR 0–4: 5291 (95.5)
k
5–14: 251 (4.5)
NR 1,850 (33.4)
No antiviral
treatment.
54,672 46,601 (85.2%)
c
25,490
(46.6)
NR 0–4: 52,345 (95.7)
5–14: 1,327 (4.3)
NR 18,138 (33.2)
Arbel et. al, 2022
[21]
Nirmatrelvir-
ritonavir for 5 days.
3,902 67.4 (11.2) 1,553 (40) NR 3,902 (100) 1,626 (42) 3,520 (90)
No antiviral
treatment.
105,352 59.6 (12.8) 41,987
(40)
NR 105,352 (100) 36,140 (34) 81,861 (78)
Schwartz et. al.,
2023 [16]
a
Nirmatrelvir-
ritonavir for 5 days.
8,876 74.3 (NI) 3,613
(40.7)
NR 3 3,805 (42.9)
<3 5,071 (57.1)
NR 8,326 (93.8)
No antiviral
treatment.
168,669 52.4 (NI) 61,733
(36.6)
NR 3 26,888 (15.9)
<3 141,781 (84.1)
NR 156,525 (92.8)
Aggarwal et al.,
2023 [24]
a
Nirmatrelvir-
ritonavir for 5 days.
7,168 18–44 years
3,288 (45.9%)
45–64 years
1,582 (22.1%)
65 years 2,298
(32.1%)
2,966
(41.4)
5,826
(81.3)
4,378 (61.1) 1,924
(26.8)
5,416 (75.5)
No antiviral
treatment.
9,361 18–44 years
5,964 (63.7%)
45–64 years
1,442 (15.4%)
65 years 1,955
(20.9%)
3,899
(41.7)
7,365
(78.7)
4,450 (47.5) 1,793
(19.2)
6,932 (74)
Najjar-Debbiny
et al., 2022 [22]
Nirmatrelvir-
ritonavir for 5 days.
4,737 68.5 (12.5) 1,992
(42.1)
NR 4,737 (100) 1,938
(40.9)
3,686 (77.8)
No antiviral
treatment.
175,614 53.9 (16.8) 71,967
(41.0)
NR 175,614 (100) 97,938
(55.8)
131,796 (75.0)
(Continued )
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Table 2. (Continued)
Study Compared
alternatives
Number of
participants
Mean age (SD). Male
n (%)
White
n (%)
Comorbidities *
n (%)
BMC 30
kg/m2
n (%)
Primary series of
COVID-19 vaccine and/
or boosters
n (%)
Qian et al., 2022
[15]
Nirmatrelvir-
ritonavir for 5 days.
307 57.1 (14.9) 72 (23.5) 259 (84.4) 260 (84.4) 27.7 (7.3)
b
299 (97.4)
No antiviral
treatment.
278 58.3 (15.6) 73 (26.3) 223 (80.2) 234 (84.2) 27.0 (8.3)
b
260 (93.5)
Shah et al., 2022
[23]
Nirmatrelvir-
ritonavir for 5 days.
198,927 18–49 years
56,620 (28.5%)
50–64 years
66,929 (33.6%)
65 years
75,378 (37.9%)
75,984
(38.2)
158,696
(79.8)
182,768 (91.9) 98,892
(49.7)
156,248 (78.5)
No antiviral
treatment.
500,921 18–49 years
221,089 (44.1%)
50–64 years
147,274 (29.4)
65 years
132,558 (26.5)
184,184
(36.8)
368,109
(73.5)
463,849 (92.6) 243,331
(48.6)
325,058 (64.9)
Bajema et. al.,
2022 [25]
a
Nirmatrelvir-
ritonavir for 5 days.
1,587 65.0 (54.0,74.0) 1,412
(89.0)
1,111
(70.0)
1,587 (100) 818 (51.5) 1,050 (66.3)
No antiviral
treatment.
1,587 66.0 (54.0,74.0) 1,416
(89.3)
1,149
(72.4)
1,587 (100) 817 (51.5) 1,035 (65.2)
Lewnard et. al.,
2023 [28]
Nirmatrelvir-
ritonavir for 5 days.
7,274 12–39 años -686
(9.4%)
40-59años-2,659
(36.6%)
60 anos 3,929
(54.0%)
3,080
(42.3)
1,921
(26.4)
3,534 (48.6) 3,253
(44.7)
6,831 (93.9)
No antiviral
treatment.
126,152 12–39 años-
44,862 (35.6%)
40–59 años-
49,864 (39.5%)
60 anos
31,425 (24.9%)
56,357
(44.7)
26,884
(21.3)
6,636 (21,1) 39,482
(31.3)
107,377 (85.1)
Zhou et. al., 2022
[29]
a
Nirmatrelvir-
ritonavir for 5 days.
2,808 60.6 (15.8) 1,183
(42.1)
2,381
(84.8)
1.38 (2.2)
h
1,214
(43.2)
1,897 (67.6)
h
No antiviral
treatment.
10,849 60.7 (16.7) 4,539
(41.8)
9,132
(84.2)
1.36 (2.3)
h
4,870
(44.9)
7,207 (66.4)
h
Patel et al., 2022
[26]
Nirmatrelvir-
ritonavir for 5 days.
337 52.6 (15.5) 178 (52.8) 227 (67.4) 337 (100) 5 (1.5)
j
301 (89.3)
No antiviral
treatment.
4,044 52.4 (17.5) 2,210
(54.7)
1,986
(49.1)
4,044 (100.0) 72 (1.8)
j
3,488 (86,3)
*Cardiovascular diseases; digestive diseases; diabetes mellitus; malignant tumor; nervous system diseases; respiratory diseases; kidney diseases; HIV infection. SD:
Standard Deviation; BMI: Body Mass Index; NR: Not Reported.
a)
Propensity Score Matching (PSM) or Weighted Analytic Cohort matched cohort;
b)
Mean BMI (SD);
c)
Studies by Wai et al., 2022 [17], Wong et al., 2022 [48] reported the number of patients over 60 and 65 years old (%);
d)
Yip et al, 2022 [14], refers to BMI data before PSM;
e)
Rate of complete vaccination specified by age and sex (% and SD);
f)
92.6% of the patients are of Chinese ethnicity.;
g)
Zhou et al., 2022 [29], vaccination status was measured considering at least one dose (1 dose);
h)
Deyo-Charlson Comorbidity Index Score;
i)
Dryden-Peterson et al., 2022 used the Monoclonal Antibody Screening Score—a comorbidity index that predicts the risk of hospitalization from COVID-19;
j)
Class 3 obesity: BMI 40 kg/m2;
k)
Charlson Comorbidity Index score.
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Table 3. Effectiveness results of studies included in the review, by subgroups.
<60 years 60 years Primary series of COVID-19
vaccine and/or boosters
n (%)
Non-vaccinated Comorbidities Without
comorbidities
Hospitalization
Aggarwal et al., 2023
[24]
a
aOR: 0.53 (0.34–
0.80)
aOR = 0.37
(0.23–0.57)
aOR = 0.47 (0.29–0.74)
d
aOR = 0.46 (0.27–
0.77)
aOR: 0.37 (0.25–
0.654)
aOR: 0.68 (0.41–
1.12)
Arbel et al., 2022
[21]
e
aHR: 0.74 (0.35 to
1.58)
aHR: 0.27 (0.15–
0.49) 65 aHR: 0.32 (0.17–0.63)
<65 años: aHR: 1.13 (0.50–2.58) 65 años: aHR: 0.15
(0.04–0.60)
<65 años: aHR: 0.23
(0.03–1.67)
Not reported NI
Shah et al., 2022 [23] 18–49: aHR: 0.59
(0.48–0.71)
50–64: aHR: 0.40
(0.34–0.58)
AHR: 0.53 (0.48–
0.58) 3 doses: aHR: 0.50 (0.45–0.55)
2 doses aHR: 0.50 (0.42–0.58)
aHR: 0.50 (0.43–0.59 1 aHR: 0.57 (0.45–
0.71)
2 aHR: 0.47 (0.44–
0.51)
aHR: 0.89 (0.58–
1.36)
Qian et al., 2022 [15] aOR: 0.07 (0.02–
0.31)
aOR: 0.11 (0.02–
0.54)
aOR: 0.09 (0.03–0.32) Not reported Not reported Not reported
Yip et. al., 2022 [14] Not reported aHR: 0. 76 (0.63–
0.92)
a
Not reported Not reported aHR: 0. 76 (0.63–
0.92)
c
Not reported
Zhou et al., 2022 [27] aHR: 0.19 (0.09,
0.38)
aHR: 0.17 (0.12,
0.26)
aHR: 0.18 (0.12, 0.28) NI Not reported Not reported
Wong et al., 2022
[48]
HR: 0.50 (0.31,
0.81)
HR: 0.80 (0.69,
0.91)
HR: 0.71 (0.51, 1.01) HR: 0.76 (0.66, 0.87) Not reported Not reported
Ganatra et al., 2022
[13]
Not reported Not reported 0.43 (0.2–0.9) Not reported Not reported Not reported
Mortality
Schwartz et al., 2022
[21]
d
OR: 0.13 (0.03–
0.57)
i
OR: 0.48 (0.39–
0.59)
1–2 doses: OR 0.23 (0.11–0.51)
3+ doses: OR 0.54 (0.43–0.67)
OR 0.34 (0.16–0.74) 3+: 0.48 (0.34–0.67)
<3: 0.50 (0.39–0.64)
Not reported
Arbel et al., 2022
[21]
b
aHR: 1.32 (0.16–
10.75)
aHR: 0.21 (0.05–
0.82)
Not reported Not reported Not reported Not reported
Wong et al., 2022
[48]
Not reported HR: 0.48 (0.32,
0.74)
Not reported HR: 0.44 (0.30, 0.66) Not reported Not reported
Mortality or hospitalization
Najjar-Debbiny et al.,
2022 [22]
aHR: 1.06 (0.36–
0.73)
aHR: 0.52 (0.36–
3.15)
aOR: 0.62 (0.39–0.98) aOR: 0.52 (0.32–0.82) Not reported Not reported
Dryden-Peterson
et al, 2022 [19]
aRR: 0.55 (0.30–
1.03)
aRR: 0.55 (0.40 to
0.77)
aRR: 0.69 (0.50–0.94) aRR: 0.19 (0.08–0.49) aRR: 0.56 (0.40 to
0.78)
e
Not reported
Bajema et al., 2022
[25]
aRR: 0.81 (0.46–
1.42)
aRR: 0.46 (0.31–
0.66)
aRR: 0.48 (0.32–0.73) aRR:0.61 (0.38–0.97) Not reported Not reported
Lewnard et. al., 2022
[28]
Not reported Not reported HR: 0.45 (0.21–0.94) Not reported Not reported Not reported
Schwartz et al., 2023
[16]
f
OR 0.34 (0.15–
0.79)
OR 0.55 (0.45–
0.66)
1–2 doses: OR 0.25 (0.12–0.50)
3+ doses: OR 0.62 (0.51–0.75)
OR 0.44 (0.23–0.84) 3+: 0.54 (0.39–0.73)
<3: 0.57 (0.46–0.71)
Not reported
a)
Aggarwal et al., 2023 –considered comorbidities 0–1 as with comorbidities;
b)
Arbel et al., 2022 [21] defined previous immunity to SARS-CoV-2 as previous vaccination or SARS-CoV-2 infection while the rest of the studies defined it only as
previous vaccination;
c)
Yip et al. al evaluated >60 years or <60 years with comorbidity;
d)
Schwartz et al., 2022 analyzed age groups <and >70 years;
e)
Dryden-Peterson et al, 2022 [19], Monoclonal Antibody Screening Score 4;
f)
iSchwartz et al., 2022 [16] analyzed age groups of <and >70 years.
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Compared to standard treatment or no antiviral treatment, nirmatrelvir-ritonavir reduced
the risk of mortality or hospitalization by 56% (OR = 0.44; 95% IC: 0.31–0.64, moderate cer-
tainty of evidence) (Fig 8).
In the subgroup analysis of vaccinated and non-vaccinated individuals, the treatment with
nirmatrelvir-ritonavir reduced the risk of mortality or hospitalization by 47% (OR = 0.53; 95%
CI: 0.39–0.72) and 58% (OR = 0.42; 95%CI: 0.24–0.73), respectively (Fig 9).
Among patients under 60 years of age, nirmatrelvir-ritonavir reduced the risk of mortality
or hospitalization by 45% (OR = 0.55; 95%CI: 0.36–0.85), while in patients over 60 years of
age, it reduced the risk by 46% (OR = 0.54; 95%CI: 0.47–0.61) (Fig 10).
Certainty of the evidence
The GRADE tool (Grading of Recommendations Assessment, Development and Evaluation)
was utilized to assess the quality of evidence. A total of 16 studies were included as evidence,
with 14 of these being meta-analyzed for the three primary outcomes of interest. All studies
Fig 2. Forest plot of all-cause mortality outcome within 35 days—Nirmatrelvir-ritonavir versus control.
https://doi.org/10.1371/journal.pone.0284006.g002
Fig 3. Forest plot of all-cause mortality outcome by vaccination status subgroup.
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demonstrated significant results in reducing the risk of death and/or hospitalization with the
use of nirmatrelvir-ritonavir (Table 4).
Regarding the hospitalization outcome within 35 days, the majority of studies exhibited a
high risk of bias, thus the overall bias risk domain was considered very serious. The domain of
inconsistency was also rated as serious, despite the absence of contrasting results, as the sum-
mary of study results revealed considerable heterogeneity (I
2
= 92%, p <0.00001). Conversely,
the remaining domains were classified as non-serious due to the absence of studies with dis-
crepant results, and we consider that the summary result was not subject to significant
imprecision.
In relation to mortality outcomes within 35 days and mortality or hospitalization within 35
days, the majority of studies exhibited a moderate risk of bias and therefore the global risk of
bias domain was considered serious. However, the remaining domains were considered non-
serious, due to the absence of discrepant results and we considered that the summary result
had no important imprecision.
Fig 4. Forest plot of all-cause mortality outcome by subgroup of agegroup.
https://doi.org/10.1371/journal.pone.0284006.g004
Fig 5. Forest plot of all-cause hospitalization outcome within 35 days—nirmatrelvir-ritonavir versus control.
https://doi.org/10.1371/journal.pone.0284006.g005
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Moreover, despite acknowledging that most studies measured mortality and hospitalization
outcomes for all causes rather than specifically for COVID-19, it was determined that the domain
of indirect evidence would be classified as non-serious for all outcomes. This decision was made
due to COVID-19 being a novel disease with poorly elucidated mechanisms, which means that
certain hospitalizations and deaths for all causes may be directly linked to COVID-19.
Regarding factors that can increase the quality of the evidence, we assessed the publication
bias of the main outcome measures by qualitatively evaluating the funnel plot. No significant
asymmetries were detected, leading us to conclude that there was no suspicion of publication
Fig 6. Forest plot of all-cause hospitalization outcome within 35 days by vaccination status subgroup.
https://doi.org/10.1371/journal.pone.0284006.g006
Fig 7. A: Forest plot of hospitalization or mortality outcome within 35 days by vaccination status subgroup. B: Forest plot of hospitalization or mortality by
subgroup of age group.
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bias. Since all the included studies used the same dose of nirmatrelvir-ritonavir, it was not pos-
sible to detect a dose-response gradient. We considered that there was no residual confound-
ing effect from observational studies that could reduce or increase the demonstrated effect.
Moreover, we determined that the magnitude of the effect was not sufficiently large to increase
the quality of the evidence.
Discussion
The aim of this systematic review and meta-analysis was to evaluate the effectiveness of nirma-
trelvir-ritonavir treatment in real-world situations, using observational studies that considered
different scenarios of the target population, who were at high risk of hospitalization, such as
vaccination status, age group, presence of comorbidities, and other associated risk factors in
patients with mild to moderate COVID-19.
This study found that nirmatrelvir-ritonavir treatment was associated with a reduced risk
of hospitalization and mortality, which is consistent with the results of previous reviews con-
ducted by Amani B et al. and Cheema et al. [6,30]. In the same direction as these results,
although with a different magnitude, Hammond et al. conducted a phase 2–3 clinical trial
(EPIC-HR) to evaluate the efficacy and safety of nirmatrelvir-ritonavir for non-hospitalized
adult patients with mild to moderate COVID-19 at high risk of severe illness, resulting in an
Fig 8. Forest plot of all-cause mortality or hospitalization outcome within 35 days—Nirmatrelvir-ritonavir versus control.
https://doi.org/10.1371/journal.pone.0284006.g008
Fig 9.
https://doi.org/10.1371/journal.pone.0284006.g009
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88.9% relative risk reduction of hospitalization or death [31]. The differences observed in the
effectiveness of nirmatrelvir-ritonavir treatment across different populations and contexts
reflect the challenges posed by significant interindividual variations in COVID-19. These vari-
ations can be influenced by factors such as individual risk, the several mutations in coronavirus
genotypes (variants), vaccination coverage, geographic location, and healthcare systems, and
can impact hospitalization criteria, timing, and treatment effectiveness. In addition to inherent
variations in study methodology, these factors make it challenging to compare studies results
across different populations and contexts [32–35]. This also means that the issue of discrepan-
cies between results from randomized controlled trials (RCTs) and observational studies can
be explained by the obvious efficacy-effectiveness gap and should not promote direct compari-
sons [36].
Aligned with the main findings, subgroup analyses comparing vaccinated and unvaccinated
patients indicated a significant reduction in the risk of mortality and hospitalization. Despite
the varied vaccination status of the studies included in this review, it was observed that some
high-risk patients did not receive a COVID-19 vaccine. In this group, treatment with nirma-
trelvir-ritonavir may confer protection against mortality and hospitalization. It is also impor-
tant to consider that despite the immunological escape of the Omicron variant, the vaccines
still provide important protection against COVID-19 [37,38]. Moreover, the Omicron variant
of COVID-19 has been demonstrated to have lower rates of hospitalization and mortality com-
pared to previous variants. These factors can affect the effect of treatment with Nirmatrelvir-
ritonavir [39,40]. Additionally, the efficacy of nirmatrelvir-ritonavir use within the context of
the availability of bivalent COVID-19 vaccines requires further consideration and evaluation.
Our meta-analysis results by age group indicate that nirmatrelvir-ritonavir treatment may
provide benefits for both younger and older COVID-19 patients in terms of hospitalization
and composite outcome of mortality or hospitalization, suggesting that the findings of this
study may be applicable to a broad population. However, in terms of mortality for population
under 60 years, the risk reduction could not be confirmed by the meta-analysis. A separate
study conducted by Arbel et al., found that only high-risk COVID-19 positive outpatients aged
65 years and older experienced reduced deaths and hospitalizations with nirmatrelvir-ritonavir
treatment. The possible reasons that explain this difference include the study period, taking
Fig 10.
https://doi.org/10.1371/journal.pone.0284006.g010
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Table 4. Summary of evidence about treatment with nirmatrelvir-ritonavir versus standard treatment (without antivirals) for COVID-19.
Certainty assessment of patients Effect Certainy Importance
of
studies
Study design Risk of
bias
Inconsistency Indirectness Imprecision Other
considerations
Nirmatrelvir-
ritonavir
Control Relative
(95% CI)
Absolute
(95% CI)
Hospitalization in 35 days
11 observational
study
very
serious
a
not serious not serious
b
not serious none 1559/234872
(0.7%)
10243/
720674
(1.4%)
OR 0.47
(0.36 to
0.61)
7 fewer per
1.000
(from 9 fewer
to 5 fewer)
⊕◯◯◯
Very low
IMPORTANT
Mortality in 35 days
13 observational
study
serious
c
not serious not serious
b
not serious none 220/242409
(0.1%)
6848/
889186
(0.8%)
OR 0.41
(0.35 to
0.52)
1 fewer per
1.000
(from 4 fewer
to 3 fewer)
⊕⊕⊕◯
Moderate
CRITICAL
Mortality or hospitalization in 35 days
5 observational
study
serious
d
not serious not serious
b
not serious none 309/22595
(1.4%)
6710/
202857
(3.3%)
OR 0.44
(0.31 to
0.64)
18 fewer per
1.000
(from 23
fewer to 12
fewer)
⊕⊕⊕◯
Moderate
CRITICAL
CI: Confidence interval; OR: Odds ratio
Explications:
a
. Most studies were at serious risk of bias, with the study by Zhou et al., 2022 [27] showing critical risk of bias for the outcome of hospitalization within 30 days using the ROBINS-I tool.
b
. Do not go down because it is mortality / hospitalization for all causes, since COVID -19 is a new disease in which all the mechanisms that cause possible hospitalizations for other causes are not
yet well understood.
c
. Most of the studies had a moderate risk of bias. However, two studies Aggarwal, et al., 2022 [24] and Patel et al., 2022 [26] showed a high risk of bias for the outcome of 30-day mortality using the
ROBINS-I tool.
d
. All studies showed a moderate risk of bias for the ROBINS-I tool
https://doi.org/10.1371/journal.pone.0284006.t004
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into account the new variants of COVID-19, hospitalization criteria for young patients, vacci-
nation status, and presence of comorbidities [21,24].
This review suggest that nirmatrelvir-ritonavir is effective in treating non vaccinated or vac-
cinated, non-severe COVID-19 patients with high risk for hospitalization. This may have
potential implications for clinicians and decision-makers and could alleviate the pressure on
the healthcare system due to COVID-19 hospitalizations. The living clinical guideline devel-
oped by the WHO makes a strong recommendation in favor of nirmatrelvir-ritonavir as the
first-choice treatment for non-severe patients with a high risk of hospital admission, and the
recent update recommends treatment for pregnant and lactating women as well [4]. Another
COVID-19 antiviral, molnupiravir (Lagevrio
1
) got a refusal of the marketing authorization by
the European Medicines Agency (EMA) on the grounds that the risk-benefit balance could not
be established and that it was not possible to identify a specific group of patients in which a
clinically relevant benefit could be demonstrated [41]. In this scenario, the therapeutic arsenal
for treating COVID-19 is more restricted.
Treating non-severe patients might be of interest, considering that antiviral drugs may be
more useful in non-severe cases of COVID-19, where viral replication is the primary mecha-
nism driving disease progression. This contrasts with severe cases, where the primary cause of
illness is an inflammatory response [42–44]. Furthermore, a randomized clinical trial con-
ducted by Liu et al. in 2023, which evaluated the efficacy of nirmatrelvir-ritonavir in adult
patients hospitalized with SARS-Cov-2 (Omicron BA.2.2 variant) infection and severe comor-
bidities, did not show any additional benefits in terms of all-cause mortality up to day 28 when
compared to standard treatment [40].
The strengths of our systematic review are several. Firstly, only ambulatory patients consid-
ered at high risk of hospitalization were included in the review. Secondly, we conducted sub-
group analyses by vaccination status and age group. Thirdly, we updated the data from the
included preprint studies that had been published at the time of article writing. Additionally,
the study was conducted in accordance with PRISMA guidelines, with the assessment of the
risk of bias according to ROBINS-I and the GRADE assessment of available evidence. We con-
ducted our search accounting for the latest publications with broad geographical distribution.
To our knowledge, this is the first systematic review with meta-analysis that highlights differ-
ences in vaccination status, age group, and comorbidity presence. Our review included studies
with heterogeneous populations as compared to the EPIC-HR trial, where 71% of the partici-
pants were Caucasians and the high-risk patients were mostly obese. This heterogeneity
increases the external validity of our results.
Our systematic review also has some limitations. Firstly, all the studies included were
retrospective cohorts, which are more prone to confounding bias. To provide more accu-
rate information on the effectiveness of nirmatrelvir-ritonavir treatment and further clarify
the findings of observational studies, it is important to have data from randomized con-
trolled trials (RCTs). The ongoing PANORAMIC trial (ISRCTN30448031) holds promise
in providing valuable insights into the treatment with nirmatrelvir-ritonavir in the current
context of COVID-19 infections [8]. However, to mitigate this limitation, most of the stud-
ies were matched by propensity score or other balancing methods between groups. Addi-
tionally, all the studies underwent assessment by the ROBINS-I bias risk tool, which
enabled us to conduct a more rigorous evaluation and determine the confidence of the
results using the GRADE method [12]. Despite these efforts, the high heterogeneity
between the studies and the subgroups evaluated, especially for the outcome of hospitaliza-
tion within 35 days, suggests the possibility of variations in criteria for patient hospitaliza-
tion decisions, different COVID-19 variants, patient characteristics, geographical location,
and other factors [34,35].
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Effectiveness of nirmatrelvir-ritonavir for the treatment of high-risk patients with COVID-19
PLOS ONE | https://doi.org/10.1371/journal.pone.0284006 October 12, 2023 18 / 23
A further limitation is that standard treatment or no use of antiviral treatment was consid-
ered as the control group in the studies. This may have affected the reported effect size and
should be considered when interpreting our results [4].
Another limitation of our study is that only a few studies could be meta-analyzed by sub-
group, which may distort the actual effect in these specific groups. To address this limitation,
we reported effect measures adjusted by studies that conducted such analyses but were not
included in the meta-analysis due to the absence of data.
The timing of antiviral therapy initiation is a critical consideration for the management of
COVID-19 patients. The World Health Organization recommends starting treatment within
five days of symptom onset [4]. However, in the studies we analyzed, the duration of symp-
toms or the date of positive COVID-19 test before treatment initiation varied widely (up to 10
days), and data on the timing of treatment initiation was often unavailable in some studies.
This lack of data poses challenges in interpreting our findings regarding the optimal timing of
oral antiviral therapy initiation. Nevertheless, the available evidence suggests that delaying the
initiation of nirmatrelvir-ritonavir therapy beyond five days of symptom onset significantly
reduces treatment efficacy against hospitalization and death [28,45]. It is important to high-
light that the beginning of treatment should be accompanied by early diagnosis, and therefore,
it is crucial that countries have access to and implement efficient testing programs, especially
in low- and middle-income countries [46].
Safety data, rebound effect and long-term outcomes of COVID-19 reported in some studies
were not included in our analysis. Hammond et al, demonstrated a lower frequency of serious
adverse events, and adverse events leading to discontinuation in the Nirmatrelvir-ritonavir
group compared to the placebo group. Similarly, the systematic review by Amani et al., dem-
onstrated that there was no significant difference in the incidence of adverse events between
the treatment and control groups in their pooled analysis (OR = 2.20; 95% CI: 0.42–11.47)
[30,31]. In addition, it should be noted that ritonavir is a CYP3A4 inhibitor, an enzyme
responsible for metabolizing several medications, and potential drug interactions should be
taken into consideration during treatment, especially among poly-treated patients and those
who are taking corticosteroids and other immunosuppressive medications [47].
Retrospective studies have suggested a low incidence of rebound phenomenon after treat-
ment with nirmatrelvir-ritonavir, which was described in a limited number of individuals, all
of whom developed virological rebound approximately between 7 and 30 days after symptom
onset and were likely infected with Omicron variants. Among patients who developed symp-
tom rebound after treatment with nirmatrelvir-ritonavir, the clinical presentation was mild
and did not require COVID-19 directed therapies [30,48–51]. It should be noted that prospec-
tive epidemiological studies are still needed to more accurately measure the incidence and risk
factors for COVID-19 rebound and compare them in those treated with nirmatrelvir-ritonavir
versus those not treated.
Finally, considering the potential benefits of treatment with nirmatrelvir-ritonavir and the
necessary precautions to guide treatment. There are challenges to consider in the healthcare
systems of countries, given that it is an expensive treatment with limited availability. There is a
need to further evaluate prioritization, cost-effectiveness and the impact of its use, especially in
low and middle-income countries [52,53].
Conclusion
The results of our meta-analysis suggest that nirmatrelvir-ritonavir could be effective in reduc-
ing hospitalization and/or mortality in high-risk individuals with COVID-19, compared to
those who did not receive antiviral treatment, either vaccinated or unvaccinated. Although it is
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Effectiveness of nirmatrelvir-ritonavir for the treatment of high-risk patients with COVID-19
PLOS ONE | https://doi.org/10.1371/journal.pone.0284006 October 12, 2023 19 / 23
important to mention that the effect on mortality reduction was uncertain for those under 60
years. The present review underscores the critical importance of early initiation of antiviral
therapy. It is crucial to acknowledge that there are still several limitations to consider, and
additional evidence is necessary to identify the subgroups of patients who may benefit the
most from this treatment. It is important to highlight that observational studies are more
prone to bias and confounding, and therefore cannot provide conclusive evidence of causality.
Data from ongoing and future randomized controlled trials may further expand our under-
standing of the efficacy and safety of nirmatrelvir-ritonavir and help improve standard treat-
ment guidelines for COVID-19.
Supporting information
S1 File. Contains PRISMA checklist, supporting materials, tables and figures.
(DOCX)
Author Contributions
Conceptualization: Kathiaja Miranda Souza, Gabriela Carrasco, Robin Rojas-Corte
´s, Mariana
Michel Barbosa, Juliana Alvares-Teodoro.
Data curation: Kathiaja Miranda Souza, Gabriela Carrasco, Mariana Michel Barbosa.
Formal analysis: Kathiaja Miranda Souza, Gabriela Carrasco, Mariana Michel Barbosa,
Eduardo Henrique Ferreira Bambirra, Juliana Alvares-Teodoro.
Investigation: Kathiaja Miranda Souza, Gabriela Carrasco.
Methodology: Kathiaja Miranda Souza, Gabriela Carrasco.
Supervision: Kathiaja Miranda Souza, Robin Rojas-Corte
´s, Jose
´Luis Castro.
Validation: Kathiaja Miranda Souza, Gabriela Carrasco, Robin Rojas-Corte
´s, Mariana Michel
Barbosa, Jose
´Luis Castro, Juliana Alvares-Teodoro.
Visualization: Kathiaja Miranda Souza, Gabriela Carrasco, Mariana Michel Barbosa, Jose
´Luis
Castro, Juliana Alvares-Teodoro.
Writing – original draft: Kathiaja Miranda Souza, Gabriela Carrasco, Mariana Michel Bar-
bosa, Juliana Alvares-Teodoro.
Writing – review & editing: Kathiaja Miranda Souza, Gabriela Carrasco, Robin Rojas-Corte
´s,
Mariana Michel Barbosa, Eduardo Henrique Ferreira Bambirra, Jose
´Luis Castro, Juliana
Alvares-Teodoro.
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PLOS ONE
Effectiveness of nirmatrelvir-ritonavir for the treatment of high-risk patients with COVID-19
PLOS ONE | https://doi.org/10.1371/journal.pone.0284006 October 12, 2023 23 / 23
