Detail
Článek
Článek online
FT
Medvik - BMČ
  • Je něco špatně v tomto záznamu ?

Novel risk stratification algorithm for estimating the risk of death in patients with relapsed multiple myeloma: external validation in a retrospective chart review

R. Hájek, S. Gonzalez-McQuire, Z. Szabo, M. Delforge, L. DeCosta, MS. Raab, W. Bouwmeester, M. Campioni, A. Briggs

. 2020 ; 10 (7) : e034209. [pub] 20200714

Jazyk angličtina Země Velká Británie

Typ dokumentu časopisecké články, práce podpořená grantem

Perzistentní odkaz   https://www.medvik.cz/link/bmc21020356

OBJECTIVES AND DESIGN: A novel risk stratification algorithm estimating risk of death in patients with relapsed multiple myeloma starting second-line treatment was recently developed using multivariable Cox regression of data from a Czech registry. It uses 16 parameters routinely collected in medical practice to stratify patients into four distinct risk groups in terms of survival expectation. To provide insight into generalisability of the risk stratification algorithm, the study aimed to validate the risk stratification algorithm using real-world data from specifically designed retrospective chart audits from three European countries. PARTICIPANTS AND SETTING: Physicians collected data from 998 patients (France, 386; Germany, 344; UK, 268) and applied the risk stratification algorithm. METHODS: The performance of the Cox regression model for predicting risk of death was assessed by Nagelkerke's R2, goodness of fit and the C-index. The risk stratification algorithm's ability to discriminate overall survival across four risk groups was evaluated using Kaplan-Meier curves and HRs. RESULTS: Consistent with the Czech registry, the stratification performance of the risk stratification algorithm demonstrated clear differentiation in risk of death between the four groups. As risk groups increased, risk of death doubled. The C-index was 0.715 (95% CI 0.690 to 0.734). CONCLUSIONS: Validation of the novel risk stratification algorithm in an independent 'real-world' dataset demonstrated that it stratifies patients in four subgroups according to survival expectation.

Citace poskytuje Crossref.org

000      
00000naa a2200000 a 4500
001      
bmc21020356
003      
CZ-PrNML
005      
20210830102049.0
007      
ta
008      
210728s2020 xxk f 000 0|eng||
009      
AR
024    7_
$a 10.1136/bmjopen-2019-034209 $2 doi
035    __
$a (PubMed)32665382
040    __
$a ABA008 $b cze $d ABA008 $e AACR2
041    0_
$a eng
044    __
$a xxk
100    1_
$a Hájek, Roman $u Department of Haematooncology, University Hospital Ostrava, Ostrava, Czech Republic roman.hajek@fno.cz
245    10
$a Novel risk stratification algorithm for estimating the risk of death in patients with relapsed multiple myeloma: external validation in a retrospective chart review / $c R. Hájek, S. Gonzalez-McQuire, Z. Szabo, M. Delforge, L. DeCosta, MS. Raab, W. Bouwmeester, M. Campioni, A. Briggs
520    9_
$a OBJECTIVES AND DESIGN: A novel risk stratification algorithm estimating risk of death in patients with relapsed multiple myeloma starting second-line treatment was recently developed using multivariable Cox regression of data from a Czech registry. It uses 16 parameters routinely collected in medical practice to stratify patients into four distinct risk groups in terms of survival expectation. To provide insight into generalisability of the risk stratification algorithm, the study aimed to validate the risk stratification algorithm using real-world data from specifically designed retrospective chart audits from three European countries. PARTICIPANTS AND SETTING: Physicians collected data from 998 patients (France, 386; Germany, 344; UK, 268) and applied the risk stratification algorithm. METHODS: The performance of the Cox regression model for predicting risk of death was assessed by Nagelkerke's R2, goodness of fit and the C-index. The risk stratification algorithm's ability to discriminate overall survival across four risk groups was evaluated using Kaplan-Meier curves and HRs. RESULTS: Consistent with the Czech registry, the stratification performance of the risk stratification algorithm demonstrated clear differentiation in risk of death between the four groups. As risk groups increased, risk of death doubled. The C-index was 0.715 (95% CI 0.690 to 0.734). CONCLUSIONS: Validation of the novel risk stratification algorithm in an independent 'real-world' dataset demonstrated that it stratifies patients in four subgroups according to survival expectation.
650    _2
$a algoritmy $7 D000465
650    _2
$a lidé $7 D006801
650    12
$a mnohočetný myelom $7 D009101
650    _2
$a retrospektivní studie $7 D012189
650    _2
$a hodnocení rizik $7 D018570
651    _2
$a Evropa $7 D005060
651    _2
$a Francie $7 D005602
651    _2
$a Německo $7 D005858
655    _2
$a časopisecké články $7 D016428
655    _2
$a práce podpořená grantem $7 D013485
700    1_
$a Gonzalez-McQuire, Sebastian $u Amgen Europe GmbH, Rotkreuz, Switzerland
700    1_
$a Szabo, Zsolt $u Amgen Europe GmbH, Rotkreuz, Switzerland
700    1_
$a Delforge, Michel $u Department of Haematology, University of Leuven, Leuven, Belgium
700    1_
$a DeCosta, Lucy $u Amgen, Uxbridge, UK
700    1_
$a Raab, Marc S $u Department of Internal Medicine, University Hospital Heidelberg, Heidelberg, Germany
700    1_
$a Bouwmeester, Walter $u Pharmerit International, Rotterdam, The Netherlands
700    1_
$a Campioni, Marco $u Amgen Europe GmbH, Rotkreuz, Switzerland
700    1_
$a Briggs, Andrew $u Institute of Health and Wellbeing, University of Glasgow, Glasgow, Scotland, UK
773    0_
$w MED00184484 $t BMJ open $x 2044-6055 $g Roč. 10, č. 7 (2020), s. e034209
856    41
$u https://pubmed.ncbi.nlm.nih.gov/32665382 $y Pubmed
910    __
$a ABA008 $b sig $c sign $y p $z 0
990    __
$a 20210728 $b ABA008
991    __
$a 20210830102050 $b ABA008
999    __
$a ok $b bmc $g 1691016 $s 1140802
BAS    __
$a 3
BAS    __
$a PreBMC
BMC    __
$a 2020 $b 10 $c 7 $d e034209 $e 20200714 $i 2044-6055 $m BMJ open $n BMJ Open $x MED00184484
LZP    __
$a Pubmed-20210728

Najít záznam

Citační ukazatele

Nahrávání dat ...

Možnosti archivace

Nahrávání dat ...