-
Je něco špatně v tomto záznamu ?
A predictive algorithm using clinical and laboratory parameters may assist in ruling out and in diagnosing MDS
HS. Oster, S. Crouch, A. Smith, G. Yu, B. Abu Shrkihe, S. Baruch, A. Kolomansky, J. Ben-Ezra, S. Naor, P. Fenaux, A. Symeonidis, R. Stauder, J. Cermak, G. Sanz, E. Hellström-Lindberg, L. Malcovati, S. Langemeijer, U. Germing, MS. Holm, K. Madry,...
Jazyk angličtina Země Spojené státy americké
Typ dokumentu časopisecké články
NLK
PubMed Central
od 2016
Europe PubMed Central
od 2016
Elsevier Open Access Journals
od 2021-10-26
ROAD: Directory of Open Access Scholarly Resources
od 2016
- MeSH
- algoritmy MeSH
- laboratoře MeSH
- lidé MeSH
- myelodysplastické syndromy * diagnóza MeSH
- nemoci kostní dřeně * MeSH
- vyšetřování kostní dřeně MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
We present a noninvasive Web-based app to help exclude or diagnose myelodysplastic syndrome (MDS), a bone marrow (BM) disorder with cytopenias and leukemic risk, diagnosed by BM examination. A sample of 502 MDS patients from the European MDS (EUMDS) registry (n > 2600) was combined with 502 controls (all BM proven). Gradient-boosted models (GBMs) were used to predict/exclude MDS using demographic, clinical, and laboratory variables. Area under the receiver operating characteristic curve (AUC), sensitivity, and specificity were used to evaluate the models, and performance was validated using 100 times fivefold cross-validation. Model stability was assessed by repeating its fit using different randomly chosen groups of 502 EUMDS cases. AUC was 0.96 (95% confidence interval, 0.95-0.97). MDS is predicted/excluded accurately in 86% of patients with unexplained anemia. A GBM score (range, 0-1) of less than 0.68 (GBM < 0.68) resulted in a negative predictive value of 0.94, that is, MDS was excluded. GBM ≥ 0.82 provided a positive predictive value of 0.88, that is, MDS. The diagnosis of the remaining patients (0.68 ≤ GBM < 0.82) is indeterminate. The discriminating variables: age, sex, hemoglobin, white blood cells, platelets, mean corpuscular volume, neutrophils, monocytes, glucose, and creatinine. A Web-based app was developed; physicians could use it to exclude or predict MDS noninvasively in most patients without a BM examination. Future work will add peripheral blood cytogenetics/genetics, EUMDS-based prospective validation, and prognostication.
Department of Haematology Aberdeen Royal Infirmary Aberdeen United Kingdom
Department of Haematology Oncology and Internal Medicine Warsaw Medical University Warsaw Poland
Department of Hematology Aarhus University Hospital Aarhus Denmark
Department of Hematology Radboudumc Nijmegen The Netherlands
Department of Internal Medicine 5 Innsbruck Medical University Innsbruck Austria
Department of Medicine Tel Aviv Sourasky Medical Center Tel Aviv Israel
Department of Pathology Tel Aviv Sourasky Medical Center Tel Aviv Israel
Division of Hematology Department of Medicine Karolinska Institutet Stockholm Sweden
Hematology Department Hospital Universitario y Politécnico La Fe Valencia Spain
Sackler Faculty of Medicine Tel Aviv University Tel Aviv Israel
Service d'Hématologie Centre Hospitalier de Perpignan Perpignan France
Service d'Hématologie Centre Hospitalier Universitaire Brabois Vandoeuvre Nancy France
St James's Institute of Oncology The Leeds Teaching Hospitals NHS Trust Leeds United Kingdom
- 000
- 00000naa a2200000 a 4500
- 001
- bmc21025092
- 003
- CZ-PrNML
- 005
- 20211026134131.0
- 007
- ta
- 008
- 211013s2021 xxu f 000 0|eng||
- 009
- AR
- 024 7_
- $a 10.1182/bloodadvances.2020004055 $2 doi
- 035 __
- $a (PubMed)34387647
- 040 __
- $a ABA008 $b cze $d ABA008 $e AACR2
- 041 0_
- $a eng
- 044 __
- $a xxu
- 100 1_
- $a Oster, Howard S $u Department of Medicine, Tel Aviv Sourasky Medical Center, Tel Aviv, Israel $u Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
- 245 12
- $a A predictive algorithm using clinical and laboratory parameters may assist in ruling out and in diagnosing MDS / $c HS. Oster, S. Crouch, A. Smith, G. Yu, B. Abu Shrkihe, S. Baruch, A. Kolomansky, J. Ben-Ezra, S. Naor, P. Fenaux, A. Symeonidis, R. Stauder, J. Cermak, G. Sanz, E. Hellström-Lindberg, L. Malcovati, S. Langemeijer, U. Germing, MS. Holm, K. Madry, A. Guerci-Bresler, D. Culligan, L. Sanhes, J. Mills, I. Kotsianidis, C. van Marrewijk, D. Bowen, T. de Witte, M. Mittelman
- 520 9_
- $a We present a noninvasive Web-based app to help exclude or diagnose myelodysplastic syndrome (MDS), a bone marrow (BM) disorder with cytopenias and leukemic risk, diagnosed by BM examination. A sample of 502 MDS patients from the European MDS (EUMDS) registry (n > 2600) was combined with 502 controls (all BM proven). Gradient-boosted models (GBMs) were used to predict/exclude MDS using demographic, clinical, and laboratory variables. Area under the receiver operating characteristic curve (AUC), sensitivity, and specificity were used to evaluate the models, and performance was validated using 100 times fivefold cross-validation. Model stability was assessed by repeating its fit using different randomly chosen groups of 502 EUMDS cases. AUC was 0.96 (95% confidence interval, 0.95-0.97). MDS is predicted/excluded accurately in 86% of patients with unexplained anemia. A GBM score (range, 0-1) of less than 0.68 (GBM < 0.68) resulted in a negative predictive value of 0.94, that is, MDS was excluded. GBM ≥ 0.82 provided a positive predictive value of 0.88, that is, MDS. The diagnosis of the remaining patients (0.68 ≤ GBM < 0.82) is indeterminate. The discriminating variables: age, sex, hemoglobin, white blood cells, platelets, mean corpuscular volume, neutrophils, monocytes, glucose, and creatinine. A Web-based app was developed; physicians could use it to exclude or predict MDS noninvasively in most patients without a BM examination. Future work will add peripheral blood cytogenetics/genetics, EUMDS-based prospective validation, and prognostication.
- 650 _2
- $a algoritmy $7 D000465
- 650 12
- $a nemoci kostní dřeně $7 D001855
- 650 _2
- $a vyšetřování kostní dřeně $7 D001856
- 650 _2
- $a lidé $7 D006801
- 650 _2
- $a laboratoře $7 D007753
- 650 12
- $a myelodysplastické syndromy $x diagnóza $7 D009190
- 655 _2
- $a časopisecké články $7 D016428
- 700 1_
- $a Crouch, Simon $u Epidemiology and Cancer Statistics Group, Department of Health Sciences, University of York, York, United Kingdom
- 700 1_
- $a Smith, Alexandra $u Epidemiology and Cancer Statistics Group, Department of Health Sciences, University of York, York, United Kingdom
- 700 1_
- $a Yu, Ge $u Epidemiology and Cancer Statistics Group, Department of Health Sciences, University of York, York, United Kingdom
- 700 1_
- $a Abu Shrkihe, Bander $u Department of Medicine, Tel Aviv Sourasky Medical Center, Tel Aviv, Israel
- 700 1_
- $a Baruch, Shoham $u Department of Cell and Developmental Biology, Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
- 700 1_
- $a Kolomansky, Albert $u Department of Medicine, Tel Aviv Sourasky Medical Center, Tel Aviv, Israel $u Department of Cell and Developmental Biology, Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
- 700 1_
- $a Ben-Ezra, Jonathan $u Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel $u Department of Pathology, Tel Aviv Sourasky Medical Center, Tel Aviv, Israel
- 700 1_
- $a Naor, Shachar $u Department of Pathology, Tel Aviv Sourasky Medical Center, Tel Aviv, Israel
- 700 1_
- $a Fenaux, Pierre $u Service d'Hématologie Séniors, Hôpital Saint-Louis, Assistance Publique des Hôpitaux de Paris (AP-HP) and Université Paris 7, Paris, France
- 700 1_
- $a Symeonidis, Argiris $u Division Hematology, Department of Internal Medicine, University of Patras Medical School, Patras, Greece
- 700 1_
- $a Stauder, Reinhard $u Department of Internal Medicine V (Hematology and Oncology), Innsbruck Medical University, Innsbruck, Austria
- 700 1_
- $a Cermak, Jaroslav $u Department of Clinical Hematology, Institute of Hematology and Blood Transfusion, Prague, Czech Republic
- 700 1_
- $a Sanz, Guillermo $u Hematology Department, Hospital Universitario y Politécnico La Fe, Valencia, Spain
- 700 1_
- $a Hellström-Lindberg, Eva $u Division of Hematology, Department of Medicine, Karolinska Institutet, Stockholm, Sweden
- 700 1_
- $a Malcovati, Luca $u Department of Molecular Medicine and Hematology Oncology, Fondazione Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS) Policlinico San Matteo, University of Pavia, Pavia, Italy
- 700 1_
- $a Langemeijer, Saskia $u Department of Hematology, Radboudumc, Nijmegen, The Netherlands
- 700 1_
- $a Germing, Ulrich $u Department of Hematology, Oncology and Clinical Immunology, Universitätsklinik Düsseldorf, Düsseldorf, Germany
- 700 1_
- $a Holm, Mette Skov $u Department of Hematology, Aarhus University Hospital, Aarhus, Denmark
- 700 1_
- $a Madry, Krzysztof $u Department of Haematology, Oncology and Internal Medicine, Warsaw Medical University, Warsaw, Poland
- 700 1_
- $a Guerci-Bresler, Agnes $u Service d'Hématologie, Centre Hospitalier Universitaire (CHU) Brabois Vandoeuvre, Nancy, France
- 700 1_
- $a Culligan, Dominic $u Department of Haematology, Aberdeen Royal Infirmary, Aberdeen, United Kingdom
- 700 1_
- $a Sanhes, Laurence $u Service d'Hématologie, Centre Hospitalier de Perpignan, Perpignan, France
- 700 1_
- $a Mills, Juliet $u Department of Haematology, Worcestershire Acute Hospitals National Health Service (NHS) Trust and University of Birmingham, Birmingham, United Kingdom
- 700 1_
- $a Kotsianidis, Ioannis $u Department of Hematology, Democritus University of Thrace Medical School, University Hospital of Alexandroupolis, Alexandroupolis, Greece
- 700 1_
- $a van Marrewijk, Corine $u Department of Hematology, Radboudumc, Nijmegen, The Netherlands
- 700 1_
- $a Bowen, David $u St. James's Institute of Oncology, The Leeds Teaching Hospitals NHS Trust, Leeds, United Kingdom; and
- 700 1_
- $a de Witte, Theo $u Department of Tumor Immunology, Nijmegen Center for Molecular Life Sciences, Radboudumc, Nijmegen, The Netherlands
- 700 1_
- $a Mittelman, Moshe $u Department of Medicine, Tel Aviv Sourasky Medical Center, Tel Aviv, Israel $u Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
- 773 0_
- $w MED00194912 $t Blood advances $x 2473-9537 $g Roč. 5, č. 16 (2021), s. 3066-3075
- 856 41
- $u https://pubmed.ncbi.nlm.nih.gov/34387647 $y Pubmed
- 910 __
- $a ABA008 $b sig $c sign $y p $z 0
- 990 __
- $a 20211013 $b ABA008
- 991 __
- $a 20211026134137 $b ABA008
- 999 __
- $a ok $b bmc $g 1714235 $s 1145599
- BAS __
- $a 3
- BAS __
- $a PreBMC
- BMC __
- $a 2021 $b 5 $c 16 $d 3066-3075 $e 20210824 $i 2473-9537 $m Blood advances $n Blood Adv $x MED00194912
- LZP __
- $a Pubmed-20211013
