Pub Date : 2023-09-07DOI: 10.1515/labmed-2023-0023
Yan Lei, Xiaolan Lu, Xiuping Duan, Wei Tang, Qiang Wang
Abstract Objectives To develop a novel diagnostic model combining bilirubin, protein induced by vitamin K absence or antagonist-II (PIVKA-II), and alpha-fetoprotein (AFP) to improve HCC diagnosis. Methods The serum levels of PIVKA-Ⅱ, AFP, and bilirubin in 718 hepatocellular carcinoma (HCC) patients and 2,763 benign liver disease (BLD) patients were measured. A mathematical model was used as the combined diagnostic model (PIVKA-Ⅱ, AFP, and bilirubin: PAB combination) for improving HCC diagnosis. Receiver operating characteristic (ROC) curves were used to analyse the diagnostic value of the individual markers, the PIVKA-II and AFP (PA) combination, and the PAB combination for HCC diagnosis. Results With the increase in bilirubin, the positive predictive value (PPV) of bilirubin in HCC diagnosis decreased (p<0.001) while the negative predictive value (NPV) increased (p<0.001). The areas under the ROC curves (AUCs) of the PAB combination were 0.935 and 0.862 for the diagnosis of HCC and HCC<3.0 cm, respectively, which were significantly higher than those of PIVKA-Ⅱ, AFP, and the PA combination (p<0.001). The AUC values for PIVKA-Ⅱ, AFP, and the PA combination were significantly decreased for the diagnosis of HCC and HCC<3.0 cm when serum levels of PIVKA-Ⅱ≥40 mAU/mL and/or AFP≥20 ng/mL were used for diagnosis, while the AUC value of the PAB combination increased. Conclusions Bilirubin is a superior biomarker for diagnosing HCC and distinguishing HCC from BLD. The combination of bilirubin with PIVKA-Ⅱ and AFP has superior diagnostic value for HCC and early-stage HCC.
{"title":"Bilirubin is a superior biomarker for hepatocellular carcinoma diagnosis and for differential diagnosis of benign liver disease","authors":"Yan Lei, Xiaolan Lu, Xiuping Duan, Wei Tang, Qiang Wang","doi":"10.1515/labmed-2023-0023","DOIUrl":"https://doi.org/10.1515/labmed-2023-0023","url":null,"abstract":"Abstract Objectives To develop a novel diagnostic model combining bilirubin, protein induced by vitamin K absence or antagonist-II (PIVKA-II), and alpha-fetoprotein (AFP) to improve HCC diagnosis. Methods The serum levels of PIVKA-Ⅱ, AFP, and bilirubin in 718 hepatocellular carcinoma (HCC) patients and 2,763 benign liver disease (BLD) patients were measured. A mathematical model was used as the combined diagnostic model (PIVKA-Ⅱ, AFP, and bilirubin: PAB combination) for improving HCC diagnosis. Receiver operating characteristic (ROC) curves were used to analyse the diagnostic value of the individual markers, the PIVKA-II and AFP (PA) combination, and the PAB combination for HCC diagnosis. Results With the increase in bilirubin, the positive predictive value (PPV) of bilirubin in HCC diagnosis decreased (p<0.001) while the negative predictive value (NPV) increased (p<0.001). The areas under the ROC curves (AUCs) of the PAB combination were 0.935 and 0.862 for the diagnosis of HCC and HCC<3.0 cm, respectively, which were significantly higher than those of PIVKA-Ⅱ, AFP, and the PA combination (p<0.001). The AUC values for PIVKA-Ⅱ, AFP, and the PA combination were significantly decreased for the diagnosis of HCC and HCC<3.0 cm when serum levels of PIVKA-Ⅱ≥40 mAU/mL and/or AFP≥20 ng/mL were used for diagnosis, while the AUC value of the PAB combination increased. Conclusions Bilirubin is a superior biomarker for diagnosing HCC and distinguishing HCC from BLD. The combination of bilirubin with PIVKA-Ⅱ and AFP has superior diagnostic value for HCC and early-stage HCC.","PeriodicalId":55986,"journal":{"name":"Journal of Laboratory Medicine","volume":null,"pages":null},"PeriodicalIF":1.2,"publicationDate":"2023-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42971359","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-08-23DOI: 10.1515/labmed-2023-0069
Xin Zhao, Jian Yang, Jun Li
Abstract Objectives The purpose of this study was to analyze the role of C-reactive protein/albumin ratio (CRP/ALB) in the diagnosis of complicated appendicitis in adults. Methods A retrospective analysis of 202 patients with acute appendicitis admitted to the Emergency Department of Weifang People’s Hospital between January 2021 and December 2022 was conducted. Patients were classified into complicated appendicitis group (CA) and non-complicated appendicitis group (NCA) based on postoperative pathological diagnosis, and the two groups were compared in terms of preoperative age, gender, white blood cell count (WBCC), C-reactive protein/albumin ratio (CRP/ALB), serum sodium (Na), and fibrinogen (FIB). Results The 202 cases of acute appendicitis in this study, 36.6 % (n=74) were CA. Multivariate logistic regression analysis showed that CPR/ALB (p≤0.001), FIB (p<0.001), and Na (p=0.011) were risk factors for complicated appendicitis. The results of receiver operating characteristic (ROC) analysis, conducted to evaluate the role of CRP/ALB, Na, and FIB in detecting CA, showed that the area under the curve (AUC) of CRP/ALB was 0.871, which was higher than that of FIB and Na. CRP/ALB ratio ≥1.04 was an important indicator for predicting complicated appendicitis, with a sensitivity of 78.2 % and specificity of 84.7 %. Conclusions CRP/ALB ratio can serve as a good indicator for predicting complicated appendicitis.
{"title":"The predictive value of the C-reactive protein/albumin ratio in adult patients with complicated appendicitis","authors":"Xin Zhao, Jian Yang, Jun Li","doi":"10.1515/labmed-2023-0069","DOIUrl":"https://doi.org/10.1515/labmed-2023-0069","url":null,"abstract":"Abstract Objectives The purpose of this study was to analyze the role of C-reactive protein/albumin ratio (CRP/ALB) in the diagnosis of complicated appendicitis in adults. Methods A retrospective analysis of 202 patients with acute appendicitis admitted to the Emergency Department of Weifang People’s Hospital between January 2021 and December 2022 was conducted. Patients were classified into complicated appendicitis group (CA) and non-complicated appendicitis group (NCA) based on postoperative pathological diagnosis, and the two groups were compared in terms of preoperative age, gender, white blood cell count (WBCC), C-reactive protein/albumin ratio (CRP/ALB), serum sodium (Na), and fibrinogen (FIB). Results The 202 cases of acute appendicitis in this study, 36.6 % (n=74) were CA. Multivariate logistic regression analysis showed that CPR/ALB (p≤0.001), FIB (p<0.001), and Na (p=0.011) were risk factors for complicated appendicitis. The results of receiver operating characteristic (ROC) analysis, conducted to evaluate the role of CRP/ALB, Na, and FIB in detecting CA, showed that the area under the curve (AUC) of CRP/ALB was 0.871, which was higher than that of FIB and Na. CRP/ALB ratio ≥1.04 was an important indicator for predicting complicated appendicitis, with a sensitivity of 78.2 % and specificity of 84.7 %. Conclusions CRP/ALB ratio can serve as a good indicator for predicting complicated appendicitis.","PeriodicalId":55986,"journal":{"name":"Journal of Laboratory Medicine","volume":null,"pages":null},"PeriodicalIF":1.2,"publicationDate":"2023-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43801526","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-08-01DOI: 10.1515/labmed-2023-frontmatter4
{"title":"Frontmatter","authors":"","doi":"10.1515/labmed-2023-frontmatter4","DOIUrl":"https://doi.org/10.1515/labmed-2023-frontmatter4","url":null,"abstract":"","PeriodicalId":55986,"journal":{"name":"Journal of Laboratory Medicine","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136072305","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abstract The present study was to evaluate the diagnostic accuracy of different types of PCR tests with the aim of determining which one performs best for detecting Helicobacter pylori in stool samples. Related articles were searched from PubMed, Embase, Web of Science databases, Scopus, and Scholar Google. The quality of included studies was assessed using the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool and RevMan5.4 software. Pooled sensitivity, specificity, DOR, PLR and NLR for the stool PCR test in detecting H. pylori infection were performed by Stata 15.0 software. Subgroup meta-analysis was performed by Open Meta-analyst software. Ten studies were selected in this study. Stool PCR test had 92.0 % (83.0, 96.0 %) pooled sensitivity, 96.0 % (84.0, 99.0 %) pooled specificity, 296.0 (51.6, 1,696.9) pooled DOR, 26.1 (5.3, 128.7) pooled PLR and 0.09 (0.04, 0.18) NLR in the diagnosis of H. pylori infection, and summary receiver operating characteristic curve (SROC) illustrated an area under the curve (AUC) of 0.98. Subgroup meta-analysis showed rtPCR as having the highest diagnostic accuracy. Our results identify rtPCR as having the highest diagnostic accuracy for the detection of H. pylori in stool samples, and the stool PCR test as a reliable diagnostic tool for H. pylori infection.
{"title":"Diagnostic accuracy of stool sample-based PCR in detecting Helicobacter pylori infection: a meta-analysis","authors":"Qinglong Zhang, Shuang Yang, Jianhua Zhou, Zhipeng Li, Lili Wang, Q. Dong","doi":"10.1515/labmed-2023-0004","DOIUrl":"https://doi.org/10.1515/labmed-2023-0004","url":null,"abstract":"Abstract The present study was to evaluate the diagnostic accuracy of different types of PCR tests with the aim of determining which one performs best for detecting Helicobacter pylori in stool samples. Related articles were searched from PubMed, Embase, Web of Science databases, Scopus, and Scholar Google. The quality of included studies was assessed using the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool and RevMan5.4 software. Pooled sensitivity, specificity, DOR, PLR and NLR for the stool PCR test in detecting H. pylori infection were performed by Stata 15.0 software. Subgroup meta-analysis was performed by Open Meta-analyst software. Ten studies were selected in this study. Stool PCR test had 92.0 % (83.0, 96.0 %) pooled sensitivity, 96.0 % (84.0, 99.0 %) pooled specificity, 296.0 (51.6, 1,696.9) pooled DOR, 26.1 (5.3, 128.7) pooled PLR and 0.09 (0.04, 0.18) NLR in the diagnosis of H. pylori infection, and summary receiver operating characteristic curve (SROC) illustrated an area under the curve (AUC) of 0.98. Subgroup meta-analysis showed rtPCR as having the highest diagnostic accuracy. Our results identify rtPCR as having the highest diagnostic accuracy for the detection of H. pylori in stool samples, and the stool PCR test as a reliable diagnostic tool for H. pylori infection.","PeriodicalId":55986,"journal":{"name":"Journal of Laboratory Medicine","volume":null,"pages":null},"PeriodicalIF":1.2,"publicationDate":"2023-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48276678","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abstract Objectives Fourth dose of SARS-CoV-2 vaccination was started from the end of May, 2022 in Japan. However, data on the precise analysis of the side effects after fourth vaccination, remain scarce. Here, we examined the side effects and the levels of SARS-CoV-2 antibody titers in healthy volunteers who underwent BNT162b2 vaccination for the fourth time. Methods Thirty-eight volunteers were assessed for the side effects of the vaccination for the fourth dose, and samples were used for the measurement of SARS-CoV-2 IgG and IgM antibody with chemiluminescent assays. Results We found that the level of IgG at day 504 (average, 117.9 AU/mL [SD 76.9]), was significantly higher than at day 264 (average, 17.3 AU/mL [SD 13.1]), which are 8 months after the third and second vaccination, respectively. The level of IgG was potently increased after fourth vaccination (average, 711.8 AU/mL [SD 361.9]), whereas IgM remained baseline level. Commonly reported side effects in the participants after the fourth dose were similar to those until third dose, such as sore arm/pain (81.0 %), generalized weakness/fatigue (57.1 %) and fever (54.8 %). The number of side effects were significantly decreased with age, and participant with sore arm/pain had higher IgG titer (p=0.0007), whereas participant with lymphadenopathy had lower IgG (p=0.0371). Conclusions The level of IgG was significantly higher in 8 months after the third, compared to the second, vaccination, and it was potently increased after fourth vaccination. The number of side effects were inversely correlated with age. Sore arm/pain and lymphadenopathy may affect IgG titer.
{"title":"Assessment of antibody titer and side effects after fourth doses of COVID-19 mRNA vaccination in 38 healthy volunteers","authors":"Rikei Kozakai, Susumu Suzuki, Yuri Sato, Mizue Takahashi, Nodoka Chida, Mei Takahashi, Kuniko Hoshi, Shin-ichiro Takahashi","doi":"10.1515/labmed-2022-0152","DOIUrl":"https://doi.org/10.1515/labmed-2022-0152","url":null,"abstract":"Abstract Objectives Fourth dose of SARS-CoV-2 vaccination was started from the end of May, 2022 in Japan. However, data on the precise analysis of the side effects after fourth vaccination, remain scarce. Here, we examined the side effects and the levels of SARS-CoV-2 antibody titers in healthy volunteers who underwent BNT162b2 vaccination for the fourth time. Methods Thirty-eight volunteers were assessed for the side effects of the vaccination for the fourth dose, and samples were used for the measurement of SARS-CoV-2 IgG and IgM antibody with chemiluminescent assays. Results We found that the level of IgG at day 504 (average, 117.9 AU/mL [SD 76.9]), was significantly higher than at day 264 (average, 17.3 AU/mL [SD 13.1]), which are 8 months after the third and second vaccination, respectively. The level of IgG was potently increased after fourth vaccination (average, 711.8 AU/mL [SD 361.9]), whereas IgM remained baseline level. Commonly reported side effects in the participants after the fourth dose were similar to those until third dose, such as sore arm/pain (81.0 %), generalized weakness/fatigue (57.1 %) and fever (54.8 %). The number of side effects were significantly decreased with age, and participant with sore arm/pain had higher IgG titer (p=0.0007), whereas participant with lymphadenopathy had lower IgG (p=0.0371). Conclusions The level of IgG was significantly higher in 8 months after the third, compared to the second, vaccination, and it was potently increased after fourth vaccination. The number of side effects were inversely correlated with age. Sore arm/pain and lymphadenopathy may affect IgG titer.","PeriodicalId":55986,"journal":{"name":"Journal of Laboratory Medicine","volume":null,"pages":null},"PeriodicalIF":1.2,"publicationDate":"2023-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48332138","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-06-12DOI: 10.1515/labmed-2023-0060
G. Hoffmann, F. Klawonn
{"title":"Applied biostatistics in laboratory medicine","authors":"G. Hoffmann, F. Klawonn","doi":"10.1515/labmed-2023-0060","DOIUrl":"https://doi.org/10.1515/labmed-2023-0060","url":null,"abstract":"","PeriodicalId":55986,"journal":{"name":"Journal of Laboratory Medicine","volume":null,"pages":null},"PeriodicalIF":1.2,"publicationDate":"2023-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48565256","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-06-02DOI: 10.1515/labmed-2023-0037
H. Witte, T. Blatter, Priyanka Nagabhushana, David Schär, James Ackermann, J. Cadamuro, A. Leichtle
Abstract The amount of data generated in the field of laboratory medicine has grown to an extent that conventional laboratory information systems (LISs) are struggling to manage and analyze this complex, entangled information (“Big Data”). Statistical learning, a generalized framework from machine learning (ML) and artificial intelligence (AI) is predestined for processing “Big Data” and holds the potential to revolutionize the field of laboratory medicine. Personalized medicine may in particular benefit from AI-based systems, especially when coupled with readily available wearables and smartphones which can collect health data from individual patients and offer new, cost-effective access routes to healthcare for patients worldwide. The amount of personal data collected, however, also raises concerns about patient-privacy and calls for clear ethical guidelines for “Big Data” research, including rigorous quality checks of data and algorithms to eliminate underlying bias and enable transparency. Likewise, novel federated privacy-preserving data processing approaches may reduce the need for centralized data storage. Generative AI-systems including large language models such as ChatGPT currently enter the stage to reshape clinical research, clinical decision-support systems, and healthcare delivery. In our opinion, AI-based systems have a tremendous potential to transform laboratory medicine, however, their opportunities should be weighed against the risks carefully. Despite all enthusiasm, we advocate for stringent added-value assessments, just as for any new drug or treatment. Human experts should carefully validate AI-based systems, including patient-privacy protection, to ensure quality, transparency, and public acceptance. In this opinion paper, data prerequisites, recent developments, chances, and limitations of statistical learning approaches are highlighted.
{"title":"Statistical learning and big data applications","authors":"H. Witte, T. Blatter, Priyanka Nagabhushana, David Schär, James Ackermann, J. Cadamuro, A. Leichtle","doi":"10.1515/labmed-2023-0037","DOIUrl":"https://doi.org/10.1515/labmed-2023-0037","url":null,"abstract":"Abstract The amount of data generated in the field of laboratory medicine has grown to an extent that conventional laboratory information systems (LISs) are struggling to manage and analyze this complex, entangled information (“Big Data”). Statistical learning, a generalized framework from machine learning (ML) and artificial intelligence (AI) is predestined for processing “Big Data” and holds the potential to revolutionize the field of laboratory medicine. Personalized medicine may in particular benefit from AI-based systems, especially when coupled with readily available wearables and smartphones which can collect health data from individual patients and offer new, cost-effective access routes to healthcare for patients worldwide. The amount of personal data collected, however, also raises concerns about patient-privacy and calls for clear ethical guidelines for “Big Data” research, including rigorous quality checks of data and algorithms to eliminate underlying bias and enable transparency. Likewise, novel federated privacy-preserving data processing approaches may reduce the need for centralized data storage. Generative AI-systems including large language models such as ChatGPT currently enter the stage to reshape clinical research, clinical decision-support systems, and healthcare delivery. In our opinion, AI-based systems have a tremendous potential to transform laboratory medicine, however, their opportunities should be weighed against the risks carefully. Despite all enthusiasm, we advocate for stringent added-value assessments, just as for any new drug or treatment. Human experts should carefully validate AI-based systems, including patient-privacy protection, to ensure quality, transparency, and public acceptance. In this opinion paper, data prerequisites, recent developments, chances, and limitations of statistical learning approaches are highlighted.","PeriodicalId":55986,"journal":{"name":"Journal of Laboratory Medicine","volume":null,"pages":null},"PeriodicalIF":1.2,"publicationDate":"2023-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41528414","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-06-01DOI: 10.1515/labmed-2023-frontmatter3
{"title":"Frontmatter","authors":"","doi":"10.1515/labmed-2023-frontmatter3","DOIUrl":"https://doi.org/10.1515/labmed-2023-frontmatter3","url":null,"abstract":"","PeriodicalId":55986,"journal":{"name":"Journal of Laboratory Medicine","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135947079","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-06-01DOI: 10.1515/labmed-2023-0042
Anne Meyer, R. Müller, Markus Hoffmann, Ø. Skadberg, A. Ladang, B. Dieplinger, Wolfgang Huf, S. Stanković, G. Kapoula, M. Orth
Abstract Objectives Indirect methods for the indirect estimation of reference intervals are increasingly being used, especially for validation of reference intervals, as they can be applied to routine patient data. In this study, we compare three statistically different indirect methods for the verification and validation of reference intervals in eight laboratories distributed throughout Europe. Methods The RefLim method is a fast and simple approach which calculates the reference intervals by extrapolating the theoretical 95 % of non-pathological values from the central linear part of a quantile-quantile plot. The TML method estimates a smoothed kernel density function for the distribution of the mixed data, for which it is assumed that the ‘‘central’’ part of the distribution represents the healthy population. The refineR utilizes an inverse modelling approach. This algorithm identifies a model that best explains the observed data before transforming the data with the Box-Cox transformation. Results We show that the different indirect methods each have their advantages but can also lead to inaccurate or ambiguous results depending on the approximation of the mathematical model to real-world data. A combination of different methodologies can improve the informative value and thus the reliability of results. Conclusions Based on routine measurements of four enzymes alkaline phosphatase (ALP), total amylase (AMY), cholinesterase (CHE) and gamma-glutamyl transferase (GGT) in adult women and men, we demonstrate that some reference limits taken from the literature need to be adapted to the laboratory’s particular local and population characteristics.
{"title":"Comparison of three indirect methods for verification and validation of reference intervals at eight medical laboratories: a European multicenter study","authors":"Anne Meyer, R. Müller, Markus Hoffmann, Ø. Skadberg, A. Ladang, B. Dieplinger, Wolfgang Huf, S. Stanković, G. Kapoula, M. Orth","doi":"10.1515/labmed-2023-0042","DOIUrl":"https://doi.org/10.1515/labmed-2023-0042","url":null,"abstract":"Abstract Objectives Indirect methods for the indirect estimation of reference intervals are increasingly being used, especially for validation of reference intervals, as they can be applied to routine patient data. In this study, we compare three statistically different indirect methods for the verification and validation of reference intervals in eight laboratories distributed throughout Europe. Methods The RefLim method is a fast and simple approach which calculates the reference intervals by extrapolating the theoretical 95 % of non-pathological values from the central linear part of a quantile-quantile plot. The TML method estimates a smoothed kernel density function for the distribution of the mixed data, for which it is assumed that the ‘‘central’’ part of the distribution represents the healthy population. The refineR utilizes an inverse modelling approach. This algorithm identifies a model that best explains the observed data before transforming the data with the Box-Cox transformation. Results We show that the different indirect methods each have their advantages but can also lead to inaccurate or ambiguous results depending on the approximation of the mathematical model to real-world data. A combination of different methodologies can improve the informative value and thus the reliability of results. Conclusions Based on routine measurements of four enzymes alkaline phosphatase (ALP), total amylase (AMY), cholinesterase (CHE) and gamma-glutamyl transferase (GGT) in adult women and men, we demonstrate that some reference limits taken from the literature need to be adapted to the laboratory’s particular local and population characteristics.","PeriodicalId":55986,"journal":{"name":"Journal of Laboratory Medicine","volume":null,"pages":null},"PeriodicalIF":1.2,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47223945","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-05-31DOI: 10.1515/labmed-2023-0033
S. Klawitter, T. Kacprowski
Abstract Reference intervals are an important component in the interpretation of medical laboratory findings. Especially in children and adolescents, their limits sometimes can change very rapidly with age. We suggest continuous methods to better represent the age-dependent progression of reference intervals. The generalized additive models for location, scale, and shape parameters (GAMLSS) from the R package gamlss generates continuous percentile plots of laboratory values. A user-friendly Shiny application called AdRI_GAMLSS (Age-dependent Reference Intervals), available at github.com/SandraKla/AdRI_GAMLSS, has been developed for this purpose. Using alkaline phosphatase (ALP) as an example, we obtain different smoothed percentile curves depending on the model used. We demonstrate the superiority of continuously modeled reference intervals compared to fixed age groups and provide the Shiny application AdRI_GAMLSS to make the technique easily accessible to clinicians and other experts.
{"title":"A visualization tool for continuous reference intervals based on GAMLSS","authors":"S. Klawitter, T. Kacprowski","doi":"10.1515/labmed-2023-0033","DOIUrl":"https://doi.org/10.1515/labmed-2023-0033","url":null,"abstract":"Abstract Reference intervals are an important component in the interpretation of medical laboratory findings. Especially in children and adolescents, their limits sometimes can change very rapidly with age. We suggest continuous methods to better represent the age-dependent progression of reference intervals. The generalized additive models for location, scale, and shape parameters (GAMLSS) from the R package gamlss generates continuous percentile plots of laboratory values. A user-friendly Shiny application called AdRI_GAMLSS (Age-dependent Reference Intervals), available at github.com/SandraKla/AdRI_GAMLSS, has been developed for this purpose. Using alkaline phosphatase (ALP) as an example, we obtain different smoothed percentile curves depending on the model used. We demonstrate the superiority of continuously modeled reference intervals compared to fixed age groups and provide the Shiny application AdRI_GAMLSS to make the technique easily accessible to clinicians and other experts.","PeriodicalId":55986,"journal":{"name":"Journal of Laboratory Medicine","volume":null,"pages":null},"PeriodicalIF":1.2,"publicationDate":"2023-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48828956","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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