Replies to perfect chronic disease diagnostic
Alverta Joseph Mikhael
The ideal specifications needed for a “perfect” chronic disease diagnostic can be described in the following points, foremost these tests need to be validated for clinical use in a CLIA (Clinical Laboratory Improvement Amendments) certified laboratory (Qin, 2019) This validation is crucial for the sake of a “perfect” diagnostic through the assurance of the assay’s accuracy, precision, analytical sensitivity and specificity, clinical sensitivity and specificity, positive predictive value (PPV), and negative predictive value (NPV). Also the in-vitro diagnostic device (IVD) needs to be reviewed by the FDA (Katsanis & Katsanis, 2013). This validation will also help in avoiding false positive and negative results. In the validation plan, samples should also be tested by at least two technologists and at different runs to evaluate margin of error during many repeats in the production sequences, the data analysis results will give information about both the reference range and the detection limit by using a SDS software (Gangisetty & Reddy, 2009). Another point is the quality control matrix which needs to be determined (that is the quality and quantity of nucleic acid needed for the assay) which will ensure the quality of test results. Furthermore, it’s important to have a validation plan that determines the positive and negative control samples which are going to be used and how many samples are needed for testing by determining the limit of detection (LOD) (Qin, 2019). Method validation and proficiency testing are further considerations also that could be performed (Rhea et al., 2011). The specific requirements for molecular test validation are dependent on the assay and typically must adhere to the established guidelines (Rhea et al., 2011). In cases of an FDA-approved test, laboratories are required only to confirm the performance specifications described in the manufacturer’s product insert (Rhea et al., 2011). The majority of LDMTs, however, are not FDA approved, and the validation of the assay’s accuracy, precision, reportable range, etc., must be established by the individual laboratory (Rhea et al., 2011). In addition, because NGS is not yet widely used for clinical diagnostic purposes, quality control standards are still being developed to address acceptable precision, accuracy, contamination, and sequence coverage parameters (Rhea et al., 2011). In the end, to summarize what makes an ideal chronic disease’s diagnostic test is that it should be rapid, effective and available, and that is mainly vindicated through proper validation procedures that can assure its qualities and actions, this will greatly answer the patients’ requirements for this diagnostic, as patients only want to receive a timely, accurate, and affordable results (Tschaggeny, 2021).
Ariella Jaffe
I think our posts had very similar content while looking at the question in two different ways! I really liked how you looked at the question through the lens of validation, and what specifications the test must have to pass the validation. Validation is an important part of the diagnostic development process, but I do not think that any test that passes validation is “perfect” and criteria for a “perfect” diagnostic could be even stricter than required by a validation (Cleophas et. al., 2008). Additionally, I really liked your mention of determining the limit of detection; I think this was a point missed in my initial post. I could be argued that there should be no limit of detection for a perfect diagnostic, where all samples no matter their concentration of test analytes could be accurately measured/diagnosed. In practice, this is not realistic, as seen with Covid-19 diagnostics, where a patients must have a certain viral load to be accurately diagnosed (Arnaout et. al., 2020).
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