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The importance of effect sizes when comparing cycle threshold values of SARS-CoV-2 variants.

ABSTRACT:

Purpose

We aimed to elaborate whether cycle threshold (Ct) values differ significantly between wild type SARS-CoV-2 (wtV) and certain viral variants and how strong or weak a potential significant effect might be.

Methods

In a retrospective study, we investigated 1873 SARS-CoV-2 positive samples for the occurrence of viral marker mutations. Age, gender, clinical setting, days after onset of symptoms, and Ct values were recorded. Statistical analysis was carried out with special consideration of effect sizes.

Results

During the study period wtV was detected in 1013 samples (54%), while 845 (45%) patients carried the Alpha variant of concern (VOC), and 15 (1%) the Beta VOC. For further analysis, only wtV and the Alpha VOC were included. In a multi-factor ANOVA and post-hoc test with Bonferroni-correction for the age groups we found significant main-effects for Ct values of the viral variant (wtV mean 26.4 (SD 4.27); Alpha VOC mean 25.0 (SD 3.84); F (1,1850) = 55.841; p < .001) and the clinical setting (outpatients: mean 25.7 (SD 4.1); inpatients: mean 27.0 (SD 4.2); F (1,1850) = 8.520, p = .004). However, since the effect sizes were very small (eta squared for the Alpha VOC = .029 and the clinical setting = .004), there was only a slight trend towards higher viral loads of the Alpha VOC compared to wtV.

Conclusions

In order to compare different variants of SARS-CoV-2 the calculation of effect sizes seems to be necessary. A combination of p-values as estimates of the existance of an effect and effect sizes as estimates of the magnitude of a potential effect may allow a better insight into transmission mechanisms of SARS-CoV-2.

SUBMITTER: Brinkmann C

PROVIDER: S-EPMC9302753 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2) cycle threshold (Ct) has been suggested as an approximate measure of initial viral burden. The utility of cycle threshold, at admission, as a predictor of disease severity has not been thoroughly investigated.Methods and findingsWe conducted a retrospective study of SARS-CoV-2 positive, hospitalized patients from 3/26/2020 to 8/5/2020 who had SARS-CoV-2 Ct data within 48 hours of admission (n = 1044). Only patients with complete survival data, discharged (n = 774) or died in hospital (n = 270), were included in our analysis. Laboratory, demographic, and clinical data were extracted from electronic medical records. Multivariable logistic regression was applied to examine the relationship of patient mortality with Ct values while adjusting for established risk factors. Ct was analyzed as continuous variable and subdivided into quartiles to better illustrate its relationship with outcome. Cumulative incidence curves were created to assess whether there was a survival difference in the setting of the competing risks of death versus patient discharge. Mean Ct at admission was higher for survivors (28.6, SD = 5.8) compared to non-survivors (24.8, SD = 6.0, P<0.001). In-hospital mortality significantly differed (p<0.05) by Ct quartile. After adjusting for age, gender, BMI, hypertension and diabetes, increased cycle threshold was associated with decreased odds of in-hospital mortality (0.91, CI 0.89-0.94, p<0.001). Compared to the 4th Quartile, patients with Ct values in the 1st Quartile (Ct <22.9) and 2nd Quartile (Ct 23.0-27.3) had an adjusted odds ratio of in-hospital mortality of 3.8 and 2.6 respectively (p<0.001). The discriminative ability of Ct to predict inpatient mortality was found to be limited, possessing an area under the curve (AUC) of 0.68 (CI 0.63-0.71).ConclusionSARS-CoV-2 Ct was found to be an independent predictor of patient mortality. However, further study is needed on how to best clinically utilize such information given the result variation due to specimen quality, phase of disease, and the limited discriminative ability of the test.