Back

What challenges remain in harmonizing cytomegalovirus viral load quantification across laboratories?

Boutolleau, D.; L'Honneur, A.-S.; Germi, R.; Chanzy, B.; Archimbaud, C.; Rzadkowolski, C.; Raimbourg, J.-B.; Gauthier, D.; Thibault, V.

2024-12-11 microbiology
10.1101/2024.12.09.627549 bioRxiv
Show abstract

Cytomegalovirus (CMV) infection monitoring is a key element in the management of immunocompromised patients. CMV DNA quantification in plasma or whole blood is the best indicator for clinicians to adjust immunosuppressive or antiviral therapies. Despite the availability of internationally standardized material, the commutability of CMV quantification results across laboratories remains inadequate. To assess inter-laboratory variability in CMV DNA quantification, we conducted a blinded study in seven independent laboratories. Each participant received a panel of 92 specimens for CMV quantification using their routinely used standard platform. While quantifications were highly correlated and reproducible, large discrepancies were observed with differences up to 1.45 log10 IU/mL between techniques for identical specimens. However, quantification scattering was lower for the WHO international standard or a commercially tested control (IQR=0.129) than for clinical specimens (0.469; p=0.0142). Blind quantification of the WHO or the commercial standard indicated that all techniques, except for fully integrated platforms, did not align well with the expected values and most platforms tended to quantify specimens and standards differently. Recalibration of all platforms against the same standard improved the spread of results, but differences of up to 1.19 log10 IU/mL remained for the same specimens. Achieving commutability in CMV quantification remains an elusive goal. Efforts should focus on improving both the assay calibrators and the run controls, which currently do not appear to simulate the unique characteristics of circulating CMV in patients. Until this is resolved, each transplanted patient should be consistently monitored by the same laboratory on the same platform.

Matching journals

The top 5 journals account for 50% of the predicted probability mass.

1
Journal of Clinical Microbiology
120 papers in training set
Top 0.1%
18.3%
2
Journal of Clinical Virology
62 papers in training set
Top 0.1%
14.2%
3
Microbiology Spectrum
435 papers in training set
Top 0.1%
9.0%
4
Diagnostic Microbiology and Infectious Disease
21 papers in training set
Top 0.1%
6.2%
5
The Journal of Infectious Diseases
182 papers in training set
Top 0.5%
6.2%
50% of probability mass above
6
The Journal of Molecular Diagnostics
36 papers in training set
Top 0.1%
3.6%
7
Journal of Medical Virology
137 papers in training set
Top 1%
3.0%
8
Clinical Chemistry
22 papers in training set
Top 0.2%
2.6%
9
Genome Medicine
154 papers in training set
Top 4%
1.9%
10
Scientific Reports
3102 papers in training set
Top 56%
1.8%
11
Nature Communications
4913 papers in training set
Top 52%
1.7%
12
Clinical Microbiology and Infection
60 papers in training set
Top 0.6%
1.7%
13
mBio
750 papers in training set
Top 8%
1.7%
14
Transfusion
18 papers in training set
Top 0.1%
1.6%
15
Frontiers in Cellular and Infection Microbiology
98 papers in training set
Top 3%
1.5%
16
Journal of Infection
71 papers in training set
Top 2%
1.5%
17
PLOS ONE
4510 papers in training set
Top 59%
1.3%
18
mSphere
281 papers in training set
Top 4%
1.2%
19
Journal of Virological Methods
36 papers in training set
Top 0.4%
1.2%
20
Emerging Infectious Diseases
103 papers in training set
Top 2%
1.1%
21
Molecular Therapy - Methods & Clinical Development
38 papers in training set
Top 0.4%
1.1%
22
eLife
5422 papers in training set
Top 52%
0.9%
23
Journal of Immunological Methods
24 papers in training set
Top 0.1%
0.9%
24
Clinical Infectious Diseases
231 papers in training set
Top 4%
0.9%
25
Pathogens
53 papers in training set
Top 1%
0.8%
26
Virus Evolution
140 papers in training set
Top 1%
0.8%
27
eBioMedicine
130 papers in training set
Top 4%
0.7%
28
Journal of General Virology
46 papers in training set
Top 0.9%
0.7%
29
Emerging Microbes & Infections
74 papers in training set
Top 2%
0.6%
30
Transplantation
13 papers in training set
Top 0.5%
0.6%