Format

Send to

Choose Destination
Bone Marrow Transplant. 2018 Apr;53(4):461-473. doi: 10.1038/s41409-017-0051-y. Epub 2018 Jan 12.

Predicting failure of hematopoietic stem cell mobilization before it starts: the predicted poor mobilizer (pPM) score.

Author information

1
Clinica di Ematologia, Università Politecnica delle Marche, Ancona, Italy.
2
UOC Medicina Interna ed Ematologia, ASUR-AV3, Civitanova Marche, Italy.
3
Ematologia-Azienda Ospedaliera San Carlo, Potenza, Italy.
4
Dipartimento di Ematologia e Oncoematologia pediatrica, Fondazione IRCCS Istituto Nazionale dei Tumori, Milano, Italy.
5
Department of Translational Medicine, University of Eastern Piedmont, Novara, Italy.
6
UOC Ematologia, Università Cattolica del Sacro Cuore, Policlinico Agostino Gemelli, Roma, Italy.
7
Clinica Ematologica, A.O. San Gerardo, Monza, Italy.
8
Hematology and Stem Cell Transplant, Azienda Ospedaliera BMM, Reggio Calabria, Italy.
9
Ematologia, AON SS Antonio e Biagio e Cesare Arrigo, Alessandria, Italy.
10
Ospedale San Raffaele, Haematology and BMT, Milano, Italy.
11
Ematologia-IFO Istituto Nazionale Tumori Regina Elena, Roma, Italy.
12
IRCCS, Centro di Riferimento Oncologico della Basilicata, Rionero in Vulture, Italy.
13
Ematologia, Università sapienza, Roma, Italy.
14
Arcispedale Santa Maria Nuova-IRCCS, Reggio Emilia, Italy.
15
UOC di Ematologia e Unità Trapianti, Osp. Antonio Perrino, Brindisi, Italy.
16
Hematology and Stem Cell Transplant, Ravenna Hospital, Ravenna, Italy.
17
UO Ematologia con Trapianto, AOU Policlinico Consorziale, Bari, Italy.
18
Dipartimento di Ematologia, Unità Trapianto di Midollo Osseo, Azienda Ospedaliera Policlinico Vittorio Emanuele, Catania, Italy.
19
Dipartimento di matematica "G. Peano", Università di Torino, Torino, Italy.
20
Clinica di Ematologia, Università Politecnica delle Marche, Ancona, Italy. a.olivieri@univpm.it.

Abstract

Predicting mobilization failure before it starts may enable patient-tailored strategies. Although consensus criteria for predicted PM (pPM) are available, their predictive performance has never been measured on real data. We retrospectively collected and analyzed 1318 mobilization procedures performed for MM and lymphoma patients in the plerixafor era. In our sample, 180/1318 (13.7%) were PM. The score resulting from published pPM criteria had sufficient performance for predicting PM, as measured by AUC (0.67, 95%CI: 0.63-0.72). We developed a new prediction model from multivariate analysis whose score (pPM-score) resulted in better AUC (0.80, 95%CI: 0.76-0.84, p < 0001). pPM-score included as risk factors: increasing age, diagnosis of NHL, positive bone marrow biopsy or cytopenias before mobilization, previous mobilization failure, priming strategy with G-CSF alone, or without upfront plerixafor. A simplified version of pPM-score was categorized using a cut-off to maximize positive likelihood ratio (15.7, 95%CI: 9.9-24.8); specificity was 98% (95%CI: 97-98.7%), sensitivity 31.7% (95%CI: 24.9-39%); positive predictive value in our sample was 71.3% (95%CI: 60-80.8%). Simplified pPM-score can "rule in" patients at very high risk for PM before starting mobilization, allowing changes in clinical management, such as choice of alternative priming strategies, to avoid highly likely mobilization failure.

PMID:
29330395
DOI:
10.1038/s41409-017-0051-y
[Indexed for MEDLINE]

Supplemental Content

Full text links

Icon for Nature Publishing Group
Loading ...
Support Center