{"doi":"10.1093/clinchem/hvab146","title":"The Truth about SARS-CoV-2 Cycle Threshold Values Is Rarely Pure and Never Simple","abstract":"Nucleic acid amplification tests (NAATs) are the reference standard methods for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) detection because of their high analytical sensitivity and specificity. Many NAATs, which use reverse transcription real-time PCR (RT-PCR), are clinically validated, technically validated, and authorized by the US Food and Drug Administration (FDA) to be interpreted qualitatively as “detected” (positive for SARS-CoV-2 RNA) or “not detected” (negative for SARS-CoV-2 RNA). As of this writing there are over 250 SARS-CoV-2 molecular diagnostic tests that have obtained emergency use authorization from the FDA. The primary results generated by RT-PCR are fluorescent light emissions; serial detection of this fluorescence is plotted and the amplification curves visualized. Positive or negative interpretation depends on whether or not the curve exceeds a specified signal threshold. Part of the resulting process includes determination of the number of cycles needed before the fluorescent signal crosses this threshold (Ct value). In general, the more viral RNA in the initial specimen, the fewer the number of amplification cycles required to generate a positive signal; thus, the lower the Ct value, the higher the viral burden in the primary sample. Though all current SARS-CoV-2 NAATs are authorized only for qualitative interpretation, as of December 10, 2020, the FDA explicitly states that the Ct value results may be reported by the clinical laboratory in addition to the qualitative interpretation. Throughout the pandemic, many scientists, physicians, politicians, and public citizens have attempted to emphasize the importance (or unimportance) of certain pandemic-related interventions, mitigation strategies, the disease itself, and testing approaches. Some have advocated that a specific variable is most important in a testing approach and should be maximized to the potential detriment of the others: detection limit and specificity, cost, turnaround time, sample type, or accessibility of collection. If the truth was obvious, then there would be little debate, but the debate has been important and earnest. As Oscar Wilde wrote, “The truth is rarely pure and never simple.” We suggest that this quote describes the current situation on the debate over the relevance of Ct values, and we will explore the clinical utility of quantitative SARS-CoV-2 testing here. Though NAAT methods remain the reference standard for the qualitative detection of SARS-CoV-2 in clinical samples, there are important nuances to consider regarding Ct values. The College of American Pathologists has urged caution in using SARS-CoV-2 Ct values for the purpose of clinical decision-making (1). Several important points were raised that illustrate the difficulty of interpreting Ct values without additional information that is typically not readily available or may not be routinely considered: (a) The amount of detectable viral RNA in a clinical specimen is impacted by multiple variables, including the specimen collection method, specimen source, transport media type and volume, duration from specimen collection to analysis, and days from infection or onset of symptoms to specimen collection; (b) Ct values can vary substantially between and within RT-PCR methods. This variability is evidenced by SARS-CoV-2 proficiency testing data, in which Ct value differences of 3 to 12 cycles were observed from the same proficiency material (1); (c) no international, commutable quantitative reference standard material that can be used to harmonize assays across laboratories exists at this time. These concerns would largely be moot, at least for individual medical centers or hospital systems, if the number of collection variables were limited and the same RT-PCR was used for all patients. However, from a practical standpoint, supply chain issues have made such a locally standardized approach difficult to achieve. Throughout the pandemic, clinical labora","journal":"Clinical Chemistry","year":2021,"id":164265,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":39,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9511,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2021-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":226843,"name":"Benjamin A. Pinsky","orcid":"0000-0001-8751-4810","position":1,"is_corresponding":false},{"id":685221,"name":"Daniel D. Rhoads","orcid":"0000-0002-7636-5191","position":0,"is_corresponding":true}],"reference_count":3,"raw_metadata":null,"created_at":"2026-07-18T23:45:27.031465Z","pmid":"34314495","pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}