Skip to main content
Leukemia Research Reports logoLink to Leukemia Research Reports
. 2019 Mar 13;11:17–20. doi: 10.1016/j.lrr.2019.03.003

Matched unrelated donor hematopoietic progenitor cell transplantation: A report based on a single registry in India

Aseem K Tiwari a, Vikash Chandra Mishra b, Apeksha Tiwari b, Pranav Dorwal c, Kapil Gupta b, Dinesh Chandra b, Vimarsh Raina b,
PMCID: PMC6434059  PMID: 30963025

Abstract

Introduction

Currently, more than 10,000 matched unrelated donor transplants (MUDT) are performed annually worldwide. India has recorded a significant increase in the number of hematopoietic progenitor cell transplantation (HPCT) centers reporting transplants. The number of HPCTs increases by approximately 10% every year, with 1878 transplants reported by Indian stem cell transplant registries in 2016. However, published outcome data of MUDT in India are scant, with reports limited to autologous and allogenic matched unrelated transplants, which motivated us to present our MUDT data.

Aims and objective

To review the operations, and more importantly, the patient outcome data of a new registry in India.

Materials and methods

We accessed an Indian HLA donor database with high-resolution HLA typing results of 7682 (until 31st July 2018) volunteer HLA donors. The typing results were uploaded to proprietary software. The search result was considered a “match” when a 10/10 potential HLA match was found. Patients who were found to be alive through mail communication and did not exhibit signs and symptoms of disease were considered to have disease-free survival (DFS).

Results

During the six years of operations of the database, 1165 searches resulted in 68 10/10 matches from the registry. Of these, 11 were MUD HPCT records. At a minimum follow-up of almost 11 months, seven recipients continue to exhibit DFS.

Conclusions

The patient DFS data prove that even a small registry with slightly more than 7000 donors can yield reasonably good patient outcomes.

Keywords: MUD, HPCT, Transplant, Disease-free survival (DFS)

1. Introduction

Hematopoietic progenitor cell transplantation (HPCT) has been established as a curative management strategy for several hematologic malignancies, including congenital and acquired disorders of the hematopoietic system [1]. HPCT is feasible only if matched related donors (MRD) are found. Only 30% of the patients find suitable MRDs as a source for HPCT. However, for patients who do not find a suitable MRD, matched unrelated donors (MUDs) can be used as the potential source for HPCT treatment [2]. Globally, more than 32 million donors are registered as MUDs [3], out of which India has a low (though annually expanding) proportion of approximately 0.35 million. Because ethnicity plays a major role in identifying a suitable MUD for subsequent successful HPCT [4], finding an HLA-matched donor in India is difficult due to its large patient population and vast ethnic diversity. A study published in 2014 revealed that the probability of finding an HLA match for an Indian patient from all the accessible global registry data was 16%; however the probability of finding a match from the Indian registries was a dismal 0.008% (donors in Indian registries were only 33,678 in 2014 compared with 22.5 million in a global HLA database called Bone Marrow Donor Worldwide) [5]. In 2008, a report revealed that 1540 Bone Marrow Transplants (BMTs) were performed at six BMT centers between 1986 and 2006 across India, but no record for MUD was available [6]. In another report, 52 HPCT centers across India reported 10,381 HPCTs between 1983 and 2015. Among these, 6240 were allogenic, whereas 4141 were autologous [7]. Even in this study[7], no data on matched unrelated donor transplants (MUDT) was available. We reviewed the operations and patient outcomes of a new HLA registry, Genebandhu [8], from its inception (May 2012) to demonstrate that suitable MUDs can be found by accessing an Indian HLA donor database.

2. Materials and methods

2.1. Donor (MUD) recruitment and registration

Genebandhu organized MUD recruitment drives at various institutions, predominantly in the north Indian states of Delhi-NCR, Haryana, Punjab, Rajasthan, and Uttarakhand. Drives were usually preceded by an awareness campaign comprising activities including one-to-many presentations, one-to-one interactions, banners, and posters. A total of 7682 (till July 31, 2018) donors were recruited and typed for HLA at high resolution (till July 31, 2018).

2.2. HLA typing and database creation

Donors were typed using a high-resolution molecular method for HLA-A, B, and C; DRB1; and DQB1. HLA allele compatibility for the HLA-A, B, and C; DRB1; and DQB1 loci was defined as a 10/10 match. The HLA typing results were uploaded to proprietary software (Prometheus). Prometheus is a specialized information system for operational activities of stem cell donor registries specifically designed by Steiner Ltd. [9] for maintaining HLA databases and allowing patients to search for donors.

2.3. Preliminary MUD search and search strategy

On receipt of a pretransplant matching request from a transplant physician, the patient's HLA type was entered in Prometheus to initiate a “donor search.” The software can find matches and displays the best-matched entries at the top of the list, with other potential donors in a descending order. The search result was considered a “match” when a potential 10/10 HLA match was found.

2.4. Formal search request

Transplant physicians planning an MUDT generate a formal search request comprising several steps in succession, as illustrated in Table 1.

Table 1.

Work flow of a formal search request.

S. No Description
1. The potential donor is contacted and asked to appear for a physical examination
2. During the physical examination, fresh blood sample is obtained, and the HLA typing is verified through confirmatory typing (CT). Samples are also examined for infectious disease markers (IDMs) (anti-HIV 1 and 2, HBsAg, anti-HCV, anti-CMV [IgM and IgG]). Moreover, tests for malaria and syphilis and a nucleic-acid amplification test for HIV, HBV, and HCV are conducted.
3. The transplant physician confirms the donor after examining CT, IDM, and physical examination records and proposes the desired type of donation (HPC-apheresis [HPC-A] or HPC-bone marrow[HPC-M])
4. The donor is contacted again and counseled for HPC donation, and written consent for donation is obtained

2.5. Collection center

Once the donor is found suitable for donation based on the physical examination, CT, and IDM test, a schedule of Granulocyte Colony Stimulating factor (GCSF) administration at 10 μg/kg body weight is planned, divided as two doses subcutaneously for four days and a single dose on the 5th day prior to harvest [10]. HPCs are collected either through apheresis (HPC-A) from the peripheral or central venous catheter or bone marrow (HPC-M). The collected HPC are transported from the collection center (CC) to transplant center (TC) through a human courier. All CC were accredited by national accreditation body (National Accreditation Board for Hospitals and Healthcare Institutions).

2.6. Transplant center

The collected HPC were transfused in specialized patient rooms with high-efficiency particulate air filters under positive pressure. The filters, positive pressure, and barrier nursing reduce the risk of infections, particularly in the myeloablative postinfusion phase before actual white blood cell (WBC) engraftment. Post-transplant immunosuppression constituted Cyclosporine and Methotrexate. Cyclosporine (5 mg/kg/day) was administered by continuous intravenous infusion as a loading dose starting on day −2. The dose was reduced to 3 mg/kg/day on day 4, and increased to 3.75 mg/kg/day from day 15 to day 35. Thereafter, patients received 5 mg/kg/day of oral cyclosporine twice a day until day 83 followed by a tapering dose until day 180. Methotrexate was administered at a dose of 15 mg/m2 on day1 and 10 mg/m2 on day 3, 6 and 11, post-infusion).

2.7. Post-transplant follow-up

A calendar of posttransplant follow-up was prepared by the TC for the 1st and 3rd months and 1st, 2nd, and 3rd years. The patient was followed up and considered to have disease-free survival (DFS) if the patient was found to be alive through mail communication with no signs and symptoms of disease.

3. Results

During the six years (May 2012–June 2018) of operations at Genebandhu, 1165 preliminary MUD search requests were received. Among these, 68 10/10 potential matches (Table 2) were identified. Out of the 68 potential matches, 25 proceeded further to the CT and IDM stages (Fig. 1). Eventually, 11 HPCTs (Table 3) materialized from the MUD database. Out of these, nine were obtained for Indian patients and two for international patients (United States and Germany). The average age of the patients was 28 (4–72) years and male to female gender was in 6:5 ratio. The clinical diagnosis was AML (n = 5), Thalassemia major (n = 2), ALL (n = 1), Aplastic anemia (n = 1), MDS (n = 1) and Myelofibrosis (n = 1). The patients had a minimum follow-up of almost 11 months. Two patients (Case No. 4 and 9) expired before engraftment due to severe bacterial infection. Two patients (Case No. 6 and 10) underwent engraftment with 100% donor chimerism but died of graft-vs-host-disease within two months after HPCT. Seven patients with almost 100% chimerism (99.6%–100%) exhibited DFS. Both cases of Thalassemia major (P5 and P8) were transfusion independent at the time of follow-up.

Table 2.

Representation of Genebandhu donor and search data (May 2012–June 2018).

Year Total number of searches Yearly increase in the number of donors Number of 10/10 matches found
2012 17 80 0
2013 109 143 3
2014 163 1477 7
2015 192 1039 9
2016 299 1081 12
2017 261 2809 26
2018(31st July 124 1053 11
Total 1165 7682 68

Fig. 1.

Fig 1

Genebandhu search data (May 2012–June 2018).

Table 3.

Characteristics of all the 11 HPCTs assisted by Genebandhu between May 2012 and June 2018.

Case Age (years) Sex Disease CD34 Counts (Million/Kg) recipient body weight Infusion date WBC Engraftment (days after infusion) Chimerism (%) Current status
P1 12 Male AML (relapse) 4.51 03/03/2014 12 99.60 Disease free
P2 72 Female AML 5.5 06/02/2015 14 100 Disease free
P3 20 Male All 3.98 14/09/2015 15 100 Disease free
P4 9 Female Aplastic anemia 49.7 31/08/2016 NA NA Expired; graft failure (day 13)
P5 4 Male Thalassemia major 7.3 12/09/2016 18 100 Transfusion free
P6 59 Male Myelofibrosis 5.3 13/03/2017 21 100 Expired; Acute GvHD (day 29)
P7 8 Male AML 14.46 17/03/2017 33 100 Disease free
P8 4 Female Thalassemia major 10.16 13/04/2017 15 100 Transfusion free
P9 35 Male MDS 10.34 07/06/2017 NA NA Expired; graft failure (day 8)
P10 58 Female AML 5.6 19/08/2017 15 NA Expired; Acute GvHD (day 40)
P11 30 Female AML 5.37 26/10/2017 13 100 Alive

Abbreviations: AML - A cute Myelogenous Leukemia; MDS - Myelodysplastic Syndrome; GvHD- Graft vs. Host disease.

4. Discussion

4.1. Autologous versus allogenic transplants

Classically, published reports have categorized transplants into autologous and allogenic. “Autologous transplants” are thought to be misnomers because they are not actually “transplants” but “bone-marrow rescue”, treatment, which usually follow high-dose chemotherapy for treatment. We also subscribe to this belief. Moreover, registry data assist only allogenic transplants and therefore, in the present study, only allogenic transplants (MUDT) were investigated.

4.2. Type of transplant and suggested algorithm

Currently, the prevalent types of transplant conducted in TCs are MRDT, MUDT, cord transplants, and haploidentical transplants, with each type having it's benefits and limitations [11]. MRDT presents advantages of being relatively inexpensive and having relatively short turn-around-times (TATs). The donor is usually a sibling of the patient and is mostly willing to donate. The patient and graft outcome results have been proven favorable [12]. Therefore, MRDT is always the first choice of transplant.

MUDT is slightly more expensive and has longer TATs because of the several steps involved in the process such as preliminary search, formal search (Table 1), harvest, and infusion [13]. Various stakeholders (TC, registry, and CC) are involved in the process. Moreover, the volunteer donor may not be immediately available for harvest. Donor attrition is also a widely reported concern [14].

Cord transplants have the advantage of being immunologically naïve, and therefore, a 6/6 match (two alleles at HLA-A, and B as well as DR each) is as good as a 10/10 match in MRDT or MUDT. However, finding a matched cord is sometimes difficult, and the dose of a single cord may be insufficient for an older child or adult patient [15].

The haploidentical transplant is becoming increasingly common because of the accessibility of the donor (parent or child), low cost, and short TATs [16].

However, studies on patient and graft outcomes in haploidentical transplants are limited. Considering the benefits and limitations of the different types of transplants, the algorithm for selecting the type should possibly be in the order MRDT > MUDT > cord transplants > haploidentical transplants. This order may change over time when we have more outcome data of haploidentical transplants, especially from our setting.

4.3. Making a difference

The present study demonstrated how a small registry with a database of approximately 7000 donors can assist in managing transplants in 11 patients. Seven patients with DFS is a reasonably good outcome, and this finding is consistent with other published reports [17]. Five Indian HLA registries registered with the World Marrow Donor Association are currently operational [18]. Because outcome data from all five registries were unavailable, the number of patients who would have benefitted may be much higher than that reported on the basis of data from a single registry (Genebandhu).

4.4. Coordination at national level

Although characteristics such as donor registration processes and search algorithms are similar among the Indian registries, organizing MUDT remains difficult for a patient (or a patient's family) because of the multiplicity of registries (five) and differences in the costs of tests and service standards among the registries. We suggest that all Indian registries be closely coordinated at the national level with uniformity at every level (such as service standards and costs). Thereafter, patient outcome data from all the five registries may be collated to obtain a nation-wide-data of the utility of HLA registries.

5. Conclusion

Collecting information on transplant activity and maintaining a database must be streamlined. To change the current scenario of HPCTs in India, stem cell registries should be actively involved in the streamlining of data, which will increase the probability of finding MUDs at lower costs and shorter TATs. This measure can make India self-reliant in finding and selecting donors for HSCTs and assist in extending the life span of hundreds of recipients. The challenges to this are the lack of awareness and government support in creating and maintaining a national stem-cell registry. Stem-cell donor registries such as Genebandhu have played an active role in improving MUD transplant rates over the past few years owing to factors such as efficient donor searches by acquiring competent technology, infrastructure, and personnel.

Funding

None.

Conflicts of interest

The authors report that they have no conflict of interest.

Acknowledgment

We are grateful to Pooja Kukreja, Ashish Sharma, Hina Solanki, Naveen Vashisht, Gaurav Bhatt, Deepak Sharma, Akhilesh Kumar, Parvind Singh, Richa Chaudhary, Archana, and Nikki for their kind support. The manuscript was edited by editingindia.com for language, grammar and syntax.

Footnotes

Supplementary material associated with this article can be found, in the online version, at doi:10.1016/j.lrr.2019.03.003.

Appendix. Supplementary materials

mmc1.xml (252B, xml)

References

  • 1.Henig I, Zuckerman T. Hematopoietic stem cell Transplantation—50 Years of evolution and future perspectives. Rambam Maimonides Med. J. 2014;5(4) doi: 10.5041/RMMJ.10162. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 2.Hurley CK, Oudshoorn M, Setterholm M. Donor registries and search strategies. Immunogenetics. Methods Mol. Biolol. 2012;882:531–547. doi: 10.1007/978-1-61779-842-9_30. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 3.https://www.wmda.info/, 2018 (Accessed on 26th June).
  • 4.Pidala J. Race/ethnicity affects the probability of finding an HLA-A, -B, - C and -DRB1 allele-matched unrelated donor and likelihood of subsequent transplant utilization. Bone Marrow Transplant. 2012;48(3):346–350. doi: 10.1038/bmt.2012.150. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 5.Tiwari A.K. Probability of finding marrow unrelated donor (MUD) for an Indian patient in a multi-national human leukocyte antigen (HLA) Registry. Indian J. Hematol. Blood Transf. 2015;31(2):186–195. doi: 10.1007/s12288-014-0416-y. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 6.Chandy M. Stem cell transplantation in India. Bone Marrow Transplant. 2008;42:S81–S84. doi: 10.1038/bmt.2008.124. Suppl 1. [DOI] [PubMed] [Google Scholar]
  • 7.Raut Shreeniwas Shilawant. Autologus stem cell transplantation for cancers: India. J. Blood Disord. Transf. 2017;8:3. [Google Scholar]
  • 8.www.genebandhu.in, 2018 (Accessed on 26th June).
  • 9.http://www.hlasoft.com/index.php/prometheus-software, 2018 (Accessed on 26th June).
  • 10.Duong HK, Savani BN, Copelan E, Devine S, Costa LJ, Wingard JR. Peripheral blood progenitor cell mobilization for autologous and allogeneic hematopoietic cell transplantation: guidelines from the American Society for Blood and Marrow Transplantation. Biol. Blood Marrow Transplant. 2014;20:1262-;73. doi: 10.1016/j.bbmt.2014.05.003. [DOI] [PubMed] [Google Scholar]
  • 11.Jeevani T. Stem cell transplantation-types, risks and benefits. J. Stem Cell Res. Therapy. 2011;1(3) [Google Scholar]
  • 12.Saber W, Opie S, Rizzo JD, Zhang MJ, Horowitz MM, Schriber J. Outcomes after matched unrelated donor vs. identical sibling hematopoietic cell transplantation (HCT) in adults with acute myelogenous leukemia (AML) Blood. 2012 doi: 10.1182/blood-2011-09-381699. 1:blood-2011. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 13.Mishra VC, Tiwari AK, Raina V, Sharma G. Timelines, an important tool for matched unrelated donor stem cell transplant: a case report and review of literature. Indian J. Transp. 2018;12(3):205. 1. [Google Scholar]
  • 14.Jervis S, Wood K, Logan A, Lee H, Poulton K. unrelated haematopoietic stem cell donor attrition rate: a manchester experience: p8. Int. J. Immunogenet. 2013;40(5):411–412. 1. [Google Scholar]
  • 15.Halagan M, Eapen M, Shaw BE, Confer D, Horowitz MM, Maiers M. Selecting optimal cord blood units: the limitations of cell dose. Blood. 2017;130:2043. [Google Scholar]
  • Kindwall-Keller TL, Ballen KK. Alternative donor graft sources for adults with hematologic malignancies: a donor for all patients in 2017. Oncologist. 2017;22(9) doi: 10.1634/theoncologist.2017-0009. 1. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 17.A1 Nademanee, GM Schmidt, Parker P, Dagis AC, Stein A, Snyder DS, O'Donnell M, Smith EP, Stepan DE, Molina A. The outcome of matched unrelated donor bone marrow transplantation in patients with hematologic malignancies using molecular typing for donor selection and graft-versus-hostdisease prophylaxis regimen of cyclosporine, methotrexate, and prednisone. Blood. 1995;86(3):1228–1234. 1. [PubMed] [Google Scholar]
  • 18.https://statistics.wmda.info/, 2018 (Accessed on 12th Septembers).

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

mmc1.xml (252B, xml)

Articles from Leukemia Research Reports are provided here courtesy of Elsevier

RESOURCES