Abstract Objectives Evaluation of the simultaneous measurement of urinary γ-glutamyltransferase (γGT) and lactate dehydrogenase (LDH) to discriminate fresh from previously frozen specimens in urine drug monitoring. Methods Two widely available photometric tests (Siemens Healthineers Atellica) were used to determine the range of urinary γGT and LDH excretion and to study the decay in urinary enzyme activity under various storage conditions (room temperature, 4–8 °C, −18 °C, −80 °C). From these data, cut-off values were established and evaluated in split (fresh/frozen) specimens. Results Both assays allow robust, reliable, and simultaneous determination of urinary γGT and LDH. In healthy subjects, the 95% reference intervals for enzyme activity in native urine were γGT: 24.4–100.4 U/g Crea (creatinine) and LDH: 2.5–45.8 U/g Crea. Frozen storage for at least 7 days at −18 °C resulted in a loss of activity to less than 50% in both enzymes. Cut-offs for frozen samples were γGT≤33.2 U/g Crea and LDH≤ 8.4 U/g Crea. When applied to 100 sample pairs (fresh/frozen), 86.5% (173/200) of the measurements were conclusive and the combination of concordant enzyme measurements (low γGT/low LDH or high γGT/high LDH) was able to predict the mode of storage with a sensitivity of 96.3% and a specificity of 96.7%. Conclusions The additional measurements of urinary γGT and LDH can be used to detect previously frozen urine specimens. A simple protocol is proposed to provide additional information on sample quality when deceit is suspected. The procedure can be easily integrated into the standard workflow of urinary drug monitoring.
{"title":"Assessment of urine sample quality by the simultaneous measurement of urinary γ-glutamyltransferase and lactate dehydrogenase enzyme activities: possible application to unravel cheating in drugs of abuse testing","authors":"Anna Friess, U. Friess, M. Shipkova, E. Wieland","doi":"10.1515/cclm-2022-0153","DOIUrl":"https://doi.org/10.1515/cclm-2022-0153","url":null,"abstract":"Abstract Objectives Evaluation of the simultaneous measurement of urinary γ-glutamyltransferase (γGT) and lactate dehydrogenase (LDH) to discriminate fresh from previously frozen specimens in urine drug monitoring. Methods Two widely available photometric tests (Siemens Healthineers Atellica) were used to determine the range of urinary γGT and LDH excretion and to study the decay in urinary enzyme activity under various storage conditions (room temperature, 4–8 °C, −18 °C, −80 °C). From these data, cut-off values were established and evaluated in split (fresh/frozen) specimens. Results Both assays allow robust, reliable, and simultaneous determination of urinary γGT and LDH. In healthy subjects, the 95% reference intervals for enzyme activity in native urine were γGT: 24.4–100.4 U/g Crea (creatinine) and LDH: 2.5–45.8 U/g Crea. Frozen storage for at least 7 days at −18 °C resulted in a loss of activity to less than 50% in both enzymes. Cut-offs for frozen samples were γGT≤33.2 U/g Crea and LDH≤ 8.4 U/g Crea. When applied to 100 sample pairs (fresh/frozen), 86.5% (173/200) of the measurements were conclusive and the combination of concordant enzyme measurements (low γGT/low LDH or high γGT/high LDH) was able to predict the mode of storage with a sensitivity of 96.3% and a specificity of 96.7%. Conclusions The additional measurements of urinary γGT and LDH can be used to detect previously frozen urine specimens. A simple protocol is proposed to provide additional information on sample quality when deceit is suspected. The procedure can be easily integrated into the standard workflow of urinary drug monitoring.","PeriodicalId":10388,"journal":{"name":"Clinical Chemistry and Laboratory Medicine (CCLM)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73020722","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
C. Buchta, J. Camp, J. Jovanović, E. Puchhammer-Stöckl, R. Strassl, MATHIAS M. MüLLER, A. Griesmacher, S. Aberle, I. Görzer
Abstract Objectives Results of earlier external quality assessment (EQA) rounds suggested remarkable differences in the sensitivity of SARS-CoV PCR assays. Although the test systems are intended to detect SARS-CoV-2 in individual samples, screening is often applied to sample pools to increase efficiency and decrease costs. However, it is unknown to what extent these tests actually meet the manufacturer’s specifications for sensitivity and how they perform when testing sample pools. Methods The sensitivity of assays in routine use was evaluated with a panel of positive samples in a round of a SARS-CoV-2 virus genome detection EQA scheme. The panel consisted of samples at or near the lower limit of detection (“weakly positive”). Laboratories that routinely test sample pools were asked to also analyze the pooled EQA samples according to their usual pool size and dilution method. Results All participants could detect a highly positive patient-derived sample (>106 copies/mL). Most (96%) of the test systems could detect at least 1,000 copies/mL, meeting the minimum acceptable benchmark, and many (94%) detected the vRNA in a sample with lower concentration (500 copies/mL). The false negative ratio increased to 16 and 26% for samples with 100 and 50 copies/mL, respectively. Conclusions The performance of most assays met or exceeded their specification on sensitivity. If assays are to be used to analyze sample pools, the sensitivity of the assay and the number of pooled samples must be balanced.
{"title":"Results of a SARS-CoV-2 virus genome detection external quality assessment round focusing on sensitivity of assays and pooling of samples","authors":"C. Buchta, J. Camp, J. Jovanović, E. Puchhammer-Stöckl, R. Strassl, MATHIAS M. MüLLER, A. Griesmacher, S. Aberle, I. Görzer","doi":"10.1515/cclm-2022-0263","DOIUrl":"https://doi.org/10.1515/cclm-2022-0263","url":null,"abstract":"Abstract Objectives Results of earlier external quality assessment (EQA) rounds suggested remarkable differences in the sensitivity of SARS-CoV PCR assays. Although the test systems are intended to detect SARS-CoV-2 in individual samples, screening is often applied to sample pools to increase efficiency and decrease costs. However, it is unknown to what extent these tests actually meet the manufacturer’s specifications for sensitivity and how they perform when testing sample pools. Methods The sensitivity of assays in routine use was evaluated with a panel of positive samples in a round of a SARS-CoV-2 virus genome detection EQA scheme. The panel consisted of samples at or near the lower limit of detection (“weakly positive”). Laboratories that routinely test sample pools were asked to also analyze the pooled EQA samples according to their usual pool size and dilution method. Results All participants could detect a highly positive patient-derived sample (>106 copies/mL). Most (96%) of the test systems could detect at least 1,000 copies/mL, meeting the minimum acceptable benchmark, and many (94%) detected the vRNA in a sample with lower concentration (500 copies/mL). The false negative ratio increased to 16 and 26% for samples with 100 and 50 copies/mL, respectively. Conclusions The performance of most assays met or exceeded their specification on sensitivity. If assays are to be used to analyze sample pools, the sensitivity of the assay and the number of pooled samples must be balanced.","PeriodicalId":10388,"journal":{"name":"Clinical Chemistry and Laboratory Medicine (CCLM)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87863693","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Effect of different incubation times on the detection of factor VIII inhibitor in acquired hemophilia A","authors":"Jiahong Zhang, R. Mu, Junli Chen, Jian-Ming Song","doi":"10.1515/cclm-2022-0046","DOIUrl":"https://doi.org/10.1515/cclm-2022-0046","url":null,"abstract":"","PeriodicalId":10388,"journal":{"name":"Clinical Chemistry and Laboratory Medicine (CCLM)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72992415","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Norman Wen Xuan Koh, C. Markus, T. P. Loh, Chun Yee Lim
Abstract Objectives Detection of between-lot reagent bias is clinically important and can be assessed by application of regression-based statistics on several paired measurements obtained from the existing and new candidate lot. Here, the bias detection capability of six regression-based lot-to-lot reagent verification assessments, including an extension of the Bland–Altman with regression approach are compared. Methods Least squares and Deming regression (in both weighted and unweighted forms), confidence ellipses and Bland–Altman with regression (BA-R) approaches were investigated. The numerical simulation included permutations of the following parameters: differing result range ratios (upper:lower measurement limits), levels of significance (alpha), constant and proportional biases, analytical coefficients of variation (CV), and numbers of replicates and sample sizes. The sample concentrations simulated were drawn from a uniformly distributed concentration range. Results At a low range ratio (1:10, CV 3%), the BA-R performed the best, albeit with a higher false rejection rate and closely followed by weighted regression approaches. At larger range ratios (1:1,000, CV 3%), the BA-R performed poorly and weighted regression approaches performed the best. At higher assay imprecision (CV 10%), all six approaches performed poorly with bias detection rates <50%. A lower alpha reduced the false rejection rate, while greater sample numbers and replicates improved bias detection. Conclusions When performing reagent lot verification, laboratories need to finely balance the false rejection rate (selecting an appropriate alpha) with the power of bias detection (appropriate statistical approach to match assay performance characteristics) and operational considerations (number of clinical samples and replicates, not having alternate reagent lot).
{"title":"Comparison of six regression-based lot-to-lot verification approaches","authors":"Norman Wen Xuan Koh, C. Markus, T. P. Loh, Chun Yee Lim","doi":"10.1515/cclm-2022-0274","DOIUrl":"https://doi.org/10.1515/cclm-2022-0274","url":null,"abstract":"Abstract Objectives Detection of between-lot reagent bias is clinically important and can be assessed by application of regression-based statistics on several paired measurements obtained from the existing and new candidate lot. Here, the bias detection capability of six regression-based lot-to-lot reagent verification assessments, including an extension of the Bland–Altman with regression approach are compared. Methods Least squares and Deming regression (in both weighted and unweighted forms), confidence ellipses and Bland–Altman with regression (BA-R) approaches were investigated. The numerical simulation included permutations of the following parameters: differing result range ratios (upper:lower measurement limits), levels of significance (alpha), constant and proportional biases, analytical coefficients of variation (CV), and numbers of replicates and sample sizes. The sample concentrations simulated were drawn from a uniformly distributed concentration range. Results At a low range ratio (1:10, CV 3%), the BA-R performed the best, albeit with a higher false rejection rate and closely followed by weighted regression approaches. At larger range ratios (1:1,000, CV 3%), the BA-R performed poorly and weighted regression approaches performed the best. At higher assay imprecision (CV 10%), all six approaches performed poorly with bias detection rates <50%. A lower alpha reduced the false rejection rate, while greater sample numbers and replicates improved bias detection. Conclusions When performing reagent lot verification, laboratories need to finely balance the false rejection rate (selecting an appropriate alpha) with the power of bias detection (appropriate statistical approach to match assay performance characteristics) and operational considerations (number of clinical samples and replicates, not having alternate reagent lot).","PeriodicalId":10388,"journal":{"name":"Clinical Chemistry and Laboratory Medicine (CCLM)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85340762","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
G. Salvagno, B. Henry, L. Pighi, S. De Nitto, Gianluca Gianfilippi, G. Lippi
{"title":"Three-month ad interim analysis of total anti-SARS-CoV-2 antibodies in healthy recipient of a single BNT162b2 vaccine booster","authors":"G. Salvagno, B. Henry, L. Pighi, S. De Nitto, Gianluca Gianfilippi, G. Lippi","doi":"10.1515/cclm-2022-0385","DOIUrl":"https://doi.org/10.1515/cclm-2022-0385","url":null,"abstract":"","PeriodicalId":10388,"journal":{"name":"Clinical Chemistry and Laboratory Medicine (CCLM)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74660444","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
M. Altilia, F. Braga, Alessia Capoferri, M. Panteghini
Measurements of serum cholinesterase (CHE, also called pseudocholinesterase) catalytic concentrations are primarily used as a test of liver function and, less frequently, as an indicator of possible organic phosphorous insecticide poisoning in agriculture or organic chemical industry workers [1]. Preoperative screening of CHE activity has been also advocated to identify individuals bearing genetic causes of enzyme deficiency in whom some muscle relaxant drugs, such as suxamethonium, administrated to aid in endotracheal intubation in surgery, may not be hydrolysed by CHE rapidly enough and cause apnea by a prolonged paralysis of respiratorymuscles [1]. Historically, many methods were proposed to measure CHE, using different acyl(thio)choline esters as substrates [2]. At present, however, all the most popular automated measuring systems use butyrylthiocholine for determining the CHE activity as this substrate provides the best reproducibility. To check the quality of CHEmeasurements it is essential to correctly define analytical performance specifications (APS). In 2014, the Strategic Conference organized by the European Federation of Clinical Chemistry and Laboratory Medicine (EFLM) proposed models for establishing APS, recommending that the choice of the most appropriate model for a specific measurand should be based on its biological and clinical characteristics [3]. Allocation of CHE to the correctmodel to derive APS can be however not easy. Although this enzyme surely plays a role in monitoring the clinical conditions mentioned above, the measurand has not a defined role in the decision making of a specific disease and test results are not interpreted through established decision limits, so that outcome-based APS cannot be defined. On the other hand, its exact biological role is unknown, and this might be a limitation for applying the model based on biological variation (BV). As CHE demonstrated rather stable concentrations in healthy individuals, it appears however rational to use the BV model to derive APS [4]. This requires the availability of reliable BVdata. Unfortunately, all the available studies evaluating CHE BV suffered important limitations, among those the collection of serial samples in enrolled individuals at a variable time distance, the derivation of the within-subject BV (CVI) without subtracting analytical variation, the analysis of samples in different batches without considering the between-run analytical variation, or the wrong inclusion of the CHE seasonal variation in CVI estimate. Table 1 summarizes the drawbacks of each published study evaluated on the basis of the compliance with the EFLM critical appraisal checklist quality items (BIVAC-QI) [5]. Maybe for these major limitations, the EFLM BV database (https://biologicalvariation.eu/) does not include CHE in the list of evaluated measurands. Therefore, we decided to perform a study assessing BV components of CHE catalytic concentration by adopting an accurately design
{"title":"Biological variation of serum cholinesterase catalytic concentrations","authors":"M. Altilia, F. Braga, Alessia Capoferri, M. Panteghini","doi":"10.1515/cclm-2022-0346","DOIUrl":"https://doi.org/10.1515/cclm-2022-0346","url":null,"abstract":"Measurements of serum cholinesterase (CHE, also called pseudocholinesterase) catalytic concentrations are primarily used as a test of liver function and, less frequently, as an indicator of possible organic phosphorous insecticide poisoning in agriculture or organic chemical industry workers [1]. Preoperative screening of CHE activity has been also advocated to identify individuals bearing genetic causes of enzyme deficiency in whom some muscle relaxant drugs, such as suxamethonium, administrated to aid in endotracheal intubation in surgery, may not be hydrolysed by CHE rapidly enough and cause apnea by a prolonged paralysis of respiratorymuscles [1]. Historically, many methods were proposed to measure CHE, using different acyl(thio)choline esters as substrates [2]. At present, however, all the most popular automated measuring systems use butyrylthiocholine for determining the CHE activity as this substrate provides the best reproducibility. To check the quality of CHEmeasurements it is essential to correctly define analytical performance specifications (APS). In 2014, the Strategic Conference organized by the European Federation of Clinical Chemistry and Laboratory Medicine (EFLM) proposed models for establishing APS, recommending that the choice of the most appropriate model for a specific measurand should be based on its biological and clinical characteristics [3]. Allocation of CHE to the correctmodel to derive APS can be however not easy. Although this enzyme surely plays a role in monitoring the clinical conditions mentioned above, the measurand has not a defined role in the decision making of a specific disease and test results are not interpreted through established decision limits, so that outcome-based APS cannot be defined. On the other hand, its exact biological role is unknown, and this might be a limitation for applying the model based on biological variation (BV). As CHE demonstrated rather stable concentrations in healthy individuals, it appears however rational to use the BV model to derive APS [4]. This requires the availability of reliable BVdata. Unfortunately, all the available studies evaluating CHE BV suffered important limitations, among those the collection of serial samples in enrolled individuals at a variable time distance, the derivation of the within-subject BV (CVI) without subtracting analytical variation, the analysis of samples in different batches without considering the between-run analytical variation, or the wrong inclusion of the CHE seasonal variation in CVI estimate. Table 1 summarizes the drawbacks of each published study evaluated on the basis of the compliance with the EFLM critical appraisal checklist quality items (BIVAC-QI) [5]. Maybe for these major limitations, the EFLM BV database (https://biologicalvariation.eu/) does not include CHE in the list of evaluated measurands. Therefore, we decided to perform a study assessing BV components of CHE catalytic concentration by adopting an accurately design","PeriodicalId":10388,"journal":{"name":"Clinical Chemistry and Laboratory Medicine (CCLM)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87026018","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Shuo Yang, Qian Zhang, Boxin Yang, Zijing Li, Wenyuan Sun, L. Cui
Abstract Objectives To validate the analytical performance and diagnostic accuracy for non-ST-segment elevation myocardial infarction (NSTEMI) with a new high-sensitivity cardiac troponin I (hs-cTnI) assay on the automated light-initiated chemiluminescent assay (LiCA®) platform. Methods Comprehensive analytical validations were performed, and the 99th percentile upper reference limit (URL) from apparently healthy individuals were established. We evaluated the diagnostic performance of the assay for NSTEMI. Results The limit of quantitation (LoQ) were 1.9 ng/L (20% CV) and 5.1 ng/L (10% CV). The sex-specific 99th percentile URLs were 17.6 ng/L (4.2% CV) for men (age 20–79y) and 14.2 ng/L (4.9% CV) for women (age 19–89y) in serum, 14.4 ng/L (4.9% CV) for men (age 19–88y) and 12.9 ng/L (5.2% CV) for women (age 19–87y) in plasma, respectively. Detection rates in healthy individuals were from 98.7 to 99.1%. The correlation coefficient and median bias between LiCA and Architect were 0.985 and 0.1% (−2.0–2.9%) in full analytical range of serum specimens. In lower range (<100 ng/L), LiCA had an overall positive bias 6.7% (−1.6–13.3%), R=0.949. At the specific medical decision levels (15.2, 26.2 and 64.0 ng/L), assay difference was estimated to be <10%. No significant differences on AUC, sensitivity and specificity, NPV and PPV were found between LiCA and Architect for the diagnosis of NSTEMI. Conclusions LiCA hs-cTnI is a precise, highly sensitive and specific assay that meets the requirement of a 3rd generation (level 4) high-sensitivity method. The diagnostic accuracy of LiCA assay for NSTEMI is comparable to the established Architect hs-cTnI assay.
{"title":"Analytical and clinical performance evaluation of a new high-sensitivity cardiac troponin I assay","authors":"Shuo Yang, Qian Zhang, Boxin Yang, Zijing Li, Wenyuan Sun, L. Cui","doi":"10.1515/cclm-2021-1136","DOIUrl":"https://doi.org/10.1515/cclm-2021-1136","url":null,"abstract":"Abstract Objectives To validate the analytical performance and diagnostic accuracy for non-ST-segment elevation myocardial infarction (NSTEMI) with a new high-sensitivity cardiac troponin I (hs-cTnI) assay on the automated light-initiated chemiluminescent assay (LiCA®) platform. Methods Comprehensive analytical validations were performed, and the 99th percentile upper reference limit (URL) from apparently healthy individuals were established. We evaluated the diagnostic performance of the assay for NSTEMI. Results The limit of quantitation (LoQ) were 1.9 ng/L (20% CV) and 5.1 ng/L (10% CV). The sex-specific 99th percentile URLs were 17.6 ng/L (4.2% CV) for men (age 20–79y) and 14.2 ng/L (4.9% CV) for women (age 19–89y) in serum, 14.4 ng/L (4.9% CV) for men (age 19–88y) and 12.9 ng/L (5.2% CV) for women (age 19–87y) in plasma, respectively. Detection rates in healthy individuals were from 98.7 to 99.1%. The correlation coefficient and median bias between LiCA and Architect were 0.985 and 0.1% (−2.0–2.9%) in full analytical range of serum specimens. In lower range (<100 ng/L), LiCA had an overall positive bias 6.7% (−1.6–13.3%), R=0.949. At the specific medical decision levels (15.2, 26.2 and 64.0 ng/L), assay difference was estimated to be <10%. No significant differences on AUC, sensitivity and specificity, NPV and PPV were found between LiCA and Architect for the diagnosis of NSTEMI. Conclusions LiCA hs-cTnI is a precise, highly sensitive and specific assay that meets the requirement of a 3rd generation (level 4) high-sensitivity method. The diagnostic accuracy of LiCA assay for NSTEMI is comparable to the established Architect hs-cTnI assay.","PeriodicalId":10388,"journal":{"name":"Clinical Chemistry and Laboratory Medicine (CCLM)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82139014","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Valentina Botondi, E. D’Adamo, M. Plebani, O. Trubiani, M. Perrotta, L. di Ricco, C. Spagnuolo, S. De Sanctis, Elisabetta Barbante, M. Strozzi, A. Maconi, Francesca Gazzolo, M. Betti, A. Roveta, Gabriella Levantini, D. Gazzolo
Abstract Perinatal sepsis constitutes a medical emergency and is still one of the major causes of mortality and morbidity. The possibility of an early diagnosis of sepsis is still debated and controversial. In particular, clinical symptoms can be hidden by the association of sepsis with other perinatal diseases and/or by therapeutic strategies performed. In this context, there is evidence that the accuracy of standard of care diagnostic parameters (i.e. blood culture, C-reactive protein, procalcitonin) can be biased by additional confounding factors (gestational age, birth-weight, acute-chronic hypoxia). Therefore, the inclusion in clinical daily practice of new biomarkers of sepsis is of utmost importance. Of a panel of biomarkers, Presepsin (P-SEP) plays an important role in the development and response of the immune system and as an early marker of sepsis both in adult and pediatric patients. Therefore, in the present review we aim to offer an overview of the role of P-SEP in the early detection of perinatal sepsis as a trustworthy marker according to actual statements of official international institutions. Future perspectives regard the possibility of a longitudinal non-invasive biological fluids P-SEP assessment thus limiting the sample stress in high risk newborns.
{"title":"Perinatal presepsin assessment: a new sepsis diagnostic tool?","authors":"Valentina Botondi, E. D’Adamo, M. Plebani, O. Trubiani, M. Perrotta, L. di Ricco, C. Spagnuolo, S. De Sanctis, Elisabetta Barbante, M. Strozzi, A. Maconi, Francesca Gazzolo, M. Betti, A. Roveta, Gabriella Levantini, D. Gazzolo","doi":"10.1515/cclm-2022-0277","DOIUrl":"https://doi.org/10.1515/cclm-2022-0277","url":null,"abstract":"Abstract Perinatal sepsis constitutes a medical emergency and is still one of the major causes of mortality and morbidity. The possibility of an early diagnosis of sepsis is still debated and controversial. In particular, clinical symptoms can be hidden by the association of sepsis with other perinatal diseases and/or by therapeutic strategies performed. In this context, there is evidence that the accuracy of standard of care diagnostic parameters (i.e. blood culture, C-reactive protein, procalcitonin) can be biased by additional confounding factors (gestational age, birth-weight, acute-chronic hypoxia). Therefore, the inclusion in clinical daily practice of new biomarkers of sepsis is of utmost importance. Of a panel of biomarkers, Presepsin (P-SEP) plays an important role in the development and response of the immune system and as an early marker of sepsis both in adult and pediatric patients. Therefore, in the present review we aim to offer an overview of the role of P-SEP in the early detection of perinatal sepsis as a trustworthy marker according to actual statements of official international institutions. Future perspectives regard the possibility of a longitudinal non-invasive biological fluids P-SEP assessment thus limiting the sample stress in high risk newborns.","PeriodicalId":10388,"journal":{"name":"Clinical Chemistry and Laboratory Medicine (CCLM)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90434667","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
L. Agnello, M. Vidali, R. V. Giglio, C. M. Gambino, Anna Maria Ciaccio, B. Lo Sasso, M. Ciaccio
Abstract Objectives Prostate cancer (PCa) represents the second most common solid cancer in men worldwide. In the last decades, the prostate health index (PHI) emerged as a reliable biomarker for detecting PCa and differentiating between non-aggressive and aggressive forms. However, before introducing it in clinical practice, more evidence is required. Thus, we performed a systematic review and meta-analysis for assessing the diagnostic performance of PHI for PCa and for detecting clinically significant PCa (csPCa). Methods Relevant publications were identified by a systematic literature search on PubMed and Web of Science from inception to January 11, 2022. Results Sixty studies, including 14,255 individuals, met the inclusion criteria for our meta-analysis. The pooled sensitivity and specificity of PHI for PCa detection was 0.791 (95%CI 0.739–0.834) and 0.625 (95%CI 0.560–0.686), respectively. The pooled sensitivity and specificity of PHI for csPCa detection was 0.874 (95%CI 0.803–0.923) and 0.569 (95%CI 0.458–0.674), respectively. Additionally, the diagnostic odds ratio was 6.302 and 9.206, respectively, for PCa and csPCa detection, suggesting moderate to good effectiveness of PHI as a diagnostic test. Conclusions PHI has a high accuracy for detecting PCa and discriminating between aggressive and non-aggressive PCa. Thus, it could be useful as a biomarker in predicting patients harbouring more aggressive cancer and guiding biopsy decisions.
{"title":"Prostate health index (PHI) as a reliable biomarker for prostate cancer: a systematic review and meta-analysis","authors":"L. Agnello, M. Vidali, R. V. Giglio, C. M. Gambino, Anna Maria Ciaccio, B. Lo Sasso, M. Ciaccio","doi":"10.1515/cclm-2022-0354","DOIUrl":"https://doi.org/10.1515/cclm-2022-0354","url":null,"abstract":"Abstract Objectives Prostate cancer (PCa) represents the second most common solid cancer in men worldwide. In the last decades, the prostate health index (PHI) emerged as a reliable biomarker for detecting PCa and differentiating between non-aggressive and aggressive forms. However, before introducing it in clinical practice, more evidence is required. Thus, we performed a systematic review and meta-analysis for assessing the diagnostic performance of PHI for PCa and for detecting clinically significant PCa (csPCa). Methods Relevant publications were identified by a systematic literature search on PubMed and Web of Science from inception to January 11, 2022. Results Sixty studies, including 14,255 individuals, met the inclusion criteria for our meta-analysis. The pooled sensitivity and specificity of PHI for PCa detection was 0.791 (95%CI 0.739–0.834) and 0.625 (95%CI 0.560–0.686), respectively. The pooled sensitivity and specificity of PHI for csPCa detection was 0.874 (95%CI 0.803–0.923) and 0.569 (95%CI 0.458–0.674), respectively. Additionally, the diagnostic odds ratio was 6.302 and 9.206, respectively, for PCa and csPCa detection, suggesting moderate to good effectiveness of PHI as a diagnostic test. Conclusions PHI has a high accuracy for detecting PCa and discriminating between aggressive and non-aggressive PCa. Thus, it could be useful as a biomarker in predicting patients harbouring more aggressive cancer and guiding biopsy decisions.","PeriodicalId":10388,"journal":{"name":"Clinical Chemistry and Laboratory Medicine (CCLM)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79865009","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Jun Zhang, Lin Chen, Qinai Xu, Y. Tao, Jie Pan, Jianmin Guo, Jing Su, Hui Xie, Yuxin Chen
Abstract Objectives Soluble programmed death-1 (sPD-1) plays an essential role in the pathogenesis and progression of various diseases, including chronic hepatitis B (CHB) and hepatocellular carcinoma (HCC). Currently, there is no Food and Drug Administration–approved sPD-1 immunoassay available for routine clinical testing. Most sPD-1 detections employed enzyme-linked immunosorbent assay (ELISA) method for research purpose, which is complicated by intensive manual operation and cannot achieve automatic detection. Therefore, we aimed to develop an automated, rapid immunoassay for sPD-1 measurement based on testing-on-a-probe (TOP) biosensors and evaluate its performance in patients with hepatic diseases. Methods We developed an automatic fluorescent immunoassay using TOP biosensors using a pair of mouse anti-PD-1 monoclonal antibodies (mAbs), which were evaluated by biolayer interferometry. The sensitivity, linearity, and repeatability of the novel immunoassay were analyzed, and its compatibility with an established ELISA kit was evaluated. Further, we quantified sPD-1 level in healthy individuals as well as patients with CHB, hepatic cirrhosis, and HCC. Results The TOP assay to quantify sPD-1 was developed and performed on an automatic fluorescent analyzer within 20 min, which showed good precision with coefficients of variation less than 10% and good linearity ranging from 2 to 3,000 pg/mL. The results tested by our TOP assay correlated well with the established ELISA assay (r=0.92, p<0.0001). Using our TOP assay, sPD-1 was significantly elevated in patients with chronic hepatitis, hepatic cirrhosis and hepatocarcinoma if compared to healthy control, respectively (p<0.0001). Conclusions An automated, rapid fluorescent immunoassay to quantify serological sPD-1 protein using TOP biosensors was developed and showed acceptable analytical performance including precision, linearity, and good correlation with the established ELISA assay, with the great potential in clinical practice.
{"title":"An automated, rapid fluorescent immunoassay to quantify serum soluble programmed death-1 (PD-1) protein using testing-on-a-probe biosensors","authors":"Jun Zhang, Lin Chen, Qinai Xu, Y. Tao, Jie Pan, Jianmin Guo, Jing Su, Hui Xie, Yuxin Chen","doi":"10.1515/cclm-2022-0166","DOIUrl":"https://doi.org/10.1515/cclm-2022-0166","url":null,"abstract":"Abstract Objectives Soluble programmed death-1 (sPD-1) plays an essential role in the pathogenesis and progression of various diseases, including chronic hepatitis B (CHB) and hepatocellular carcinoma (HCC). Currently, there is no Food and Drug Administration–approved sPD-1 immunoassay available for routine clinical testing. Most sPD-1 detections employed enzyme-linked immunosorbent assay (ELISA) method for research purpose, which is complicated by intensive manual operation and cannot achieve automatic detection. Therefore, we aimed to develop an automated, rapid immunoassay for sPD-1 measurement based on testing-on-a-probe (TOP) biosensors and evaluate its performance in patients with hepatic diseases. Methods We developed an automatic fluorescent immunoassay using TOP biosensors using a pair of mouse anti-PD-1 monoclonal antibodies (mAbs), which were evaluated by biolayer interferometry. The sensitivity, linearity, and repeatability of the novel immunoassay were analyzed, and its compatibility with an established ELISA kit was evaluated. Further, we quantified sPD-1 level in healthy individuals as well as patients with CHB, hepatic cirrhosis, and HCC. Results The TOP assay to quantify sPD-1 was developed and performed on an automatic fluorescent analyzer within 20 min, which showed good precision with coefficients of variation less than 10% and good linearity ranging from 2 to 3,000 pg/mL. The results tested by our TOP assay correlated well with the established ELISA assay (r=0.92, p<0.0001). Using our TOP assay, sPD-1 was significantly elevated in patients with chronic hepatitis, hepatic cirrhosis and hepatocarcinoma if compared to healthy control, respectively (p<0.0001). Conclusions An automated, rapid fluorescent immunoassay to quantify serological sPD-1 protein using TOP biosensors was developed and showed acceptable analytical performance including precision, linearity, and good correlation with the established ELISA assay, with the great potential in clinical practice.","PeriodicalId":10388,"journal":{"name":"Clinical Chemistry and Laboratory Medicine (CCLM)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-05-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76550883","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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