Additional plerixafor to granulocyte colony-stimulating factors for haematopoietic stem cell mobilisation for autologous transplantation in malignant lymphoma or multiple myeloma patients

  • Protocol
  • Intervention

Authors

  • Tim Hartmann,

    1. University of Cologne, Cochrane Haematological Malignancies Group, Department I of Internal Medicine, Cologne, Germany
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  • Kai Hübel,

    1. University Hospital of Cologne, Department I of Internal Medicine, Center of Integrated Oncology Köln Bonn, Cologne, Germany
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  • Ina Monsef,

    1. University Hospital of Cologne, Cochrane Haematological Malignancies Group, Department I of Internal Medicine, Cologne, Germany
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  • Andreas Engert,

    1. University Hospital of Cologne, Cochrane Haematological Malignancies Group, Department I of Internal Medicine, Cologne, Germany
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  • Nicole Skoetz

    Corresponding author
    1. University Hospital of Cologne, Cochrane Haematological Malignancies Group, Department I of Internal Medicine, Cologne, Germany
    • Nicole Skoetz, Cochrane Haematological Malignancies Group, Department I of Internal Medicine, University Hospital of Cologne, Kerpener Str. 62, Cologne, 50924, Germany. nicole.skoetz@uk-koeln.de.

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Abstract

This is the protocol for a review and there is no abstract. The objectives are as follows:

To evaluate the efficacy and safety of plerixafor for the mobilisation of haematopoietic stem cells in people with non-Hodgkin lymphoma (NHL), Hodgkin lymphoma (HL) and multiple myeloma (MM) with the indication for autologous transplantation.

Background

Description of the condition

Malignant lymphomas are malignancies of the lymph nodes and lymphatic system with possible involvement of other organs, and can be differentiated into non-Hodgkin lymphoma (NHL) and Hodgkin lymphoma (HL). Multiple myeloma (MM) is a malignancy of the bone marrow and is classified among the plasma cell neoplasms by the World Health Organization (WHO).

Non-Hodgkin lymphoma derives from B and T lymphocytes or natural killer (NK) cells at varying stages of maturation. The most common classification of NHL is the WHO system which was last updated in 2008. It classifies the NHL in B-cell neoplasms and T/NK-cell neoplasms, whereby about 85% of the NHL descend from mature and progenitor B lymphocytes (Herold 2013; Jaffe 2009). A clinical approach is the classification to indolent NHL (approximately 70% of all NHL) and aggressive NHL (approximately 30% of all NHLs) (Herold 2013). The annual incidence of NHL varies between different regions in the world. In North America the incidence is estimated to be 13.7 per 100,000 inhabitants, while in the European Union it is 8.3 per 100,000 inhabitants, with the global incidence amounting to 5.1 per 100,000 inhabitants. The worldwide mortality is 2.5% and is quite similar in the various global regions (GLOBOCAN 2008). The median age at diagnosis is around 60 years, and varies only slightly between the diverse types of NHL (Herold 2013).

Hodgkin lymphoma arises from germinal centre or post-germinal centre B cells, and is associated with unique neoplastic cells called Sternberg-Reed cells which morphologically differentiate HL from NHL. The WHO classifies HL into the classic (approximately 93% of all HL) and the nodular lymphocyte predominant (approximately 7% of all HL) type (Gobbi 2013; Herold 2013). Hodgkin lymphoma accounts for about 10% of all lymphomas and has an annual incidence of 2 to 3 per 100,000 inhabitants in Western countries (Jemal 2009; Sant 2010; Smith 2011). Hence HL is a comparatively rare disease, but it is one of the most common malignancies in young adults. In industrialised countries the age distribution of HL shows a first peak in the third decade and a second peak around the age of 60 (Herold 2013).

Multiple myeloma, one of the mature B-cell neoplasms, is characterised by the accumulation of malignant plasma cells in the bone marrow compartment, by the increased production of a monoclonal immunoglobulin (Ig), and bone destruction. This disorder may be preceded by a pre-malignant state called monoclonal gammopathy of undetermined significance. Overall, MM accounts for approximately 10% of all haematologic malignancies and for 1% of all cancers (Siegel 2012). The annual incidence is approximately 4 to 5 per 100,000 inhabitants in Western countries (Phekoo 2004; Sant 2010; Smith 2011). Multiple myeloma is an adult-onset disease, with a median age at diagnosis of 66 and only 2% of patients younger than 40 years of age (Kyle 2003). To date, no curative approach exists for MM, and depending on the therapy the overall survival varies between a few months and some years. The 10-year survival rate of young patients with ideal treatment is around 50% (Herold 2013).

Description of the intervention

High-dose chemotherapy in combination with autologous stem cell transplantation is widely used as an effective treatment option for people with NHL, HL and MM (Greb 2008; Naumann-Winter 2012; Rancea 2011; Schaaf 2012). Stem cell transplantation is directed at restoring a functioning bone marrow in patients after myeloablative chemotherapy. In contrast to allogeneic transplantation with donor cells, in the autologous setting stem cells are collected from the patient and re-infused after the high-dose chemotherapy (Jantunen 2012).

Commonly-used agents for stem cell mobilisation are granulocyte colony-stimulating factors (G-CSF). The patient receives G-CSF for up to eight days and as soon as sufficient CD34-positive cells are detectable in the patient's peripheral blood, the stem cells are collected by stem cell harvest (aphereses) and stored for transplantation after the myeloablative therapy (Jantunen 2012). The two types of traditional mobilisation methods, G-CSF with chemotherapy (chemo-mobilisation) or without chemotherapy ('steady-state') leads to a failure rate of 5% to 40% of the cases, depending on definition, disease and mobilisation agents used (Jantunen 2010). In contrast to G-CSF mobilisation alone, chemo-mobilisation leads to higher stem cell yield, a higher probability of getting grafts with a large number of CD34+ cells, fewer aphereses and even to an anti-tumour effect. But chemo-mobilisation is associated with higher toxicity and increased probability of complications (Bensinger 2009; Gertz 2010). Major risk factors for mobilisation failure are advanced age, the diagnosis of NHL, progressive disease, previous radiotherapy, bone marrow involvement or prior treatment with lenalidomide or purine analogues, thrombocytopenia, and the failure of previous mobilisation attempts (Basak 2011; Malard 2011).

Plerixafor is a new agent, which apparently improves mobilisation and stem cell harvest, and reduces the required number of aphereses (Jantunen 2010). It has mainly been studied in combination with G-CSF mobilisation. Before its approval in Europe, plerixafor was only available at transplant centres in the compassionate use program (CUP). Positive results of this programme evaluating plerixafor in combination with G-CSF in patients who had previously failed a mobilisation attempt (60% to 75%) strongly indicate the efficacy of this agent (Basak 2011; Hubel 2011). Based on promising data from phase II studies, randomised controlled trials (RCTs) were initiated comparing G-CSF in combination with plerixafor to G-CSF and placebo (DiPersio 2009a; DiPersio 2009b).

How the intervention might work

Plerixafor (formerly AMD3100) was originally developed for the treatment of HIV infection. It inhibits the CXCR4 chemokine receptor that blocks the receptor binding of the stromal cell–derived factor-1α. This interaction leads to the mobilisation of haematopoietic stem cells from the bone marrow into the peripheral blood, in mice as well as in humans (Broxmeyer 2005; Hatse 2003; Maziarz 2013). Moreover, plerixafor and G-CSF are synergistic. Results of clinical trials indicate that plerixafor plus G-CSF leads to an increased augmentation of mobilisation and release of CD34+ cells into the peripheral blood, facilitating effective apheresis (Bensinger 2009).

Why it is important to do this review

Even though a Health Technology Assessment (HTA) report of the Ludwig Boltzmann Institute is already evaluating the role of plerixafor (Hintringer 2010), this proposed systematic review will be of high relevance because a new systematic literature search will be performed and recent research results will be included. At the time of publication of the HTA report in March 2010, at least two clinical trials were still ongoing and not completed. For the HTA report no new systematic literature search was run, and it only evaluated the evidence used during the European approval process in the European Public Assessment Report (EPAR) of the European Medicines Agency (EMA) already published in 2009.

Based on the published trials plerixafor might be an effective mobilisation agent in the treatment of people with NHL, HL in relapse and MM. A systematic review and meta-analysis will provide the conclusive evidence to clarify the role of this agent and will also examine differences of treatment effectiveness caused by population group or chemotherapy agents. To choose the best therapeutic options, evidence is needed for decisions at individual patient level as well as for decisions in the health care system.

Objectives

To evaluate the efficacy and safety of plerixafor for the mobilisation of haematopoietic stem cells in people with non-Hodgkin lymphoma (NHL), Hodgkin lymphoma (HL) and multiple myeloma (MM) with the indication for autologous transplantation.

Methods

Criteria for considering studies for this review

Types of studies

We will include only randomised controlled trials (RCTs). We will exclude cross-over trials and quasi-randomised trials.We will include full-text and also abstracts and unpublished data if sufficient information on study design, participant characteristics, interventions and outcomes is available.

Types of participants

We will examine patients with histologically confirmed diagnosis of NHL, HL or MM requiring high-dose chemotherapy followed by autologous stem cell transplantation, without age or gender restriction. We will consider all stages and subtypes of malignant lymphoma or multiple myeloma, including newly diagnosed patients and relapsed patients or patients with resistant disease.

Types of interventions

We will evaluate additional plerixafor compared to placebo or no additional therapy for stem cell mobilisation.

Apart from the experimental/control intervention, participants in both groups must have been intended to receive identical treatment for stem cell mobilisation (e.g. granulocyte colony-stimulating factors (G-CSF)) and supportive care.

Types of outcome measures

Primary outcomes
  • Overall survival

  • Successful stem cell collection

Secondary outcomes
  • Progression-free survival

  • Proportion of participants achieving the optimal CD34+ cell target for transplantation

  • Time to engraftment

  • Quality of life, if measured with reliable and valid instruments

  • Adverse events

Search methods for identification of studies

We will use search strategies based on those described in Chapter 6 of the Cochrane Handbook for Systematic Reviews of Interventions (Lefebvre 2011). We will not use any language constraints.

Electronic searches

We will search the following electronic databases:

  • Cochrane Central Register of Controlled Trials (CENTRAL) (The Cochrane Library, latest issue) (see Appendix 1)

  • MEDLINE (1990 to present, for search strategy see Appendix 2)

Searching other resources

We will search conference proceedings of the following annual meetings which are not included in CENTRAL for abstracts:

  • American Society of Hematology (ASH) from 2005 to present

  • American Society of Clinical Oncology (ASCO) from 2005 to present

  • European Hematology Association (EHA) from 2005 to present

  • American Society for Blood and Marrow Transplantation (ASBMT) from 2005 to present

  • European Group for Blood and Marrow Transplantation (EBMT) from 2005 to present

We will electronically search the database of ongoing trials:

  • Metaregister of controlled trials: www.controlled-trials.com/mrct/

We will handsearch the following references:

  • References of all identified trials, relevant review articles and current treatment guidelines

Data collection and analysis

Selection of studies

Two review authors will independently screen the results of the search strategies for eligibility for this review by reading the abstracts. In the case of disagreement we will obtain the full-text publication. If no consensus can be reached, we will consult a third review author, in accordance with the Higgins 2011, Chapter 7.

We will document the study selection process in a flow chart as recommended in the PRISMA statement (Moher 2009), showing the total numbers of retrieved references and the numbers of included and excluded studies.

Data extraction and management

Two review authors will independently extract the data according to the guidelines proposed by the Higgins 2011. We will contact authors of individual studies for additional information, if required. We will use a standardised data extraction form containing the following items:

  • General information: author, title, source, publication date, country, language, duplicate publications.

  • Quality assessment: sequence generation, allocation concealment, blinding (participants, personnel, outcome assessors), incomplete outcome data, selective outcome reporting, other potential sources of bias.

  • Study characteristics: trial design, aims, setting and dates, source of participants, inclusion/exclusion criteria, comparability of groups, subgroup analysis, statistical methods, power calculations, treatment cross-overs, compliance with assigned treatment, length of follow-up, time point of randomisation.

  • Participant characteristics: underlying disease, stage of disease, histological subtype, additional diagnoses, age, gender, ethnicity, number of participants recruited/allocated/evaluated, participants lost to follow-up, type of treatment (multi-agent chemotherapy (intensity of regimen, number of cycles), additional radiotherapy).

  • Interventions: type, duration and intensity of plerixafor.

  • Outcomes: overall survival, progression-free survival, proportion of participants achieving the optimal CD34+ cell target for transplantation, time to engraftment, quality of life, adverse events.

Assessment of risk of bias in included studies

Two review authors (NS and SF) will independently assess the risk of bias for each study using the following criteria outlined in the Higgins 2011b, Chapter 8.

  • Sequence generation

  • Allocation concealment

  • Blinding (participants, personnel, outcome assessors)

  • Incomplete outcome data

  • Selective outcome reporting

  • Other potential sources of bias

We will make a judgement for every criterion, using one of three categories.

  1. 'Low risk': if the criterion is adequately fulfilled in the study, i.e. the study is at a low risk of bias for the given criterion.

  2. 'High risk': if the criterion is not fulfilled in the study, i.e. the study is at high risk of bias for the given criterion.

  3. 'Unclear': if the study report does not provide sufficient information to allow for a judgement of 'Yes' or 'No', or if the risk of bias is unknown for one of the criteria listed above.

Measures of treatment effect

We will use intention-to-treat data. For binary outcomes, we will calculate risk ratios (RRs) with 95% confidence intervals (CIs) for each trial. For time-to-event outcomes, we will extract hazard ratios (HRs) from published data according to Parmar and Tierney (Parmar 1998; Tierney 2007). We will calculate continuous outcomes as standardised mean differences.

Dealing with missing data

As suggested in Chapter 16 of the Higgins 2011a, there are many potential sources of missing data which have to be taken into account: at study level, at outcome level, and at summary data level. Firstly, it is important to distinguish between 'missing at random' and 'not missing at random'. We will contact the original investigators to request missing data. If data are still missing, we will make explicit assumptions of any methods used; for example, that the data are assumed to be missing at random or that missing values are assumed to have a particular value, such as a poor outcome. We will impute missing data for participants who were lost to follow-up after randomisation (dichotomous data) assuming poor outcome ('worst-case scenario') for missing individuals. We will perform sensitivity analysis to assess how sensitive results are to reasonable changes in the assumptions that are made. We will address the potential impact of missing data on the findings of the review in the discussion.

Assessment of heterogeneity

We will assess heterogeneity of treatment effects between trials by using a Chi² test with a significance level at P < 0.1. We will use the I² statistic to quantify possible heterogeneity (I² > 30% moderate heterogeneity, I² > 75% considerable heterogeneity) (Deeks 2011). We will explore potential causes of heterogeneity by sensitivity and subgroup analyses.

Assessment of reporting biases

In meta-analyses with at least 10 trials included in an outcome, we will explore potential publication bias by generating a funnel plot and statistically test this by using a linear regression test (Sterne 2011). We will consider a P value of less than 0.1 to be significant for this test.

Data synthesis

Should the data be considered sufficiently similar to be combined, we will pool results by applying meta-analyses using the fixed-effect model, and will use the random-effects model as a sensitivity analysis. If the trials are clinically too heterogeneous to combine, we will perform subgroup analyses only without calculating an overall estimate. We will perform analyses according to the recommendations of The Cochrane Collaboration (Deeks 2011) and will use the Cochrane statistical package Review Manager 5 for analysis (Review Manager (RevMan)).

We will create a 'Summary of findings' table on absolute risks in each group with the help of the GRADE programme, and will use it to summarise the evidence of overall survival, quality of life, progression-free survival, time to engraftment and adverse effects. For clinical interpretation, we will calculate numbers needed to treat for an additional beneficial outcome (NNTB) and numbers needed to treat for an additional harmful outcome (NNTH), with corresponding 95% CIs.

Subgroup analysis and investigation of heterogeneity

We will consider performing subgroup analyses using the following characteristics:

  • Age (< 60 years, ≥ 60 years)

  • Gender (male, female)

  • Underlying disease (non-Hodgkin lymphoma, multiple myeloma, Hodgkin lymphoma)

  • Therapy (first-line, relapse therapy) of underlying disease

  • Dosage of plerixafor

  • Additional drugs for mobilisation (e.g. G-CSF)

Sensitivity analysis

We will perform sensitivity analyses using quality criteria:

  • Quality components with regard to low and high risk of bias

  • Fixed-effect modelling versus random-effects modelling.

Acknowledgements

We would like to thank the following members of the Cochrane Haematological Malignancies Group (CHMG) for their comments and improving the protocol: Guido Schwarzer, Sebastian Theurich (Editors), Céline Fournier (Consumer Editor), Andrea Will (Editorial Base).

Appendices

Appendix 1. CENTRAL search strategy

Search
MeSH descriptor Lymphoma explode all trees
lymphom*
linfom*
MeSH descriptor Hematologic Neoplasms explode all trees
(hemato* NEAR/5 malign* ) or (hemato* NEAR/5 neoplas*) or (haemato* NEAR/5 malign* ) or (haemato* NEAR/5 neoplas*)
MeSH descriptor Lymphoma, Non-Hodgkin explode all trees
(non-hodgkin* or non hodgkin* or nonhodgkin* or no hodgkin* or nhl)
(lymph* NEAR/2 sarcom*)
lymphosarcom*
(reticulum-cell* NEAR/2 sarcom*) or (reticulum cell* NEAR/2 sarcom*)
reticul*sarcom*
MeSH descriptor Hodgkin Disease explode all trees
Germinoblastom*
Reticulolymphosarcom*
Hodgkin*
(malignan* NEAR/2 granulom*) or (malignan* NEAR/2 lymphogranulom*)
MeSH descriptor Multiple Myeloma explode all trees
myelom*
MeSH descriptor Plasmacytoma explode all trees
plasm*cytom*
plasmozytom*
plasm* cell myelom*
myelomatosis
MeSH descriptor Leukemia, Plasma Cell explode all trees
plasma* NEAR/3 neoplas*
kahler*
(#1 OR #2 OR #3 OR #4 OR #5 OR #6 OR #7 OR #8 OR #9 OR #10 OR #11 OR #12 OR #13 OR #14 OR #15 OR #16 OR #17 OR #18 OR #19 OR #20 OR #21 OR #22 OR #23 OR #24 OR #25 OR #26)
MeSH descriptor Receptors, CXCR4 explode all trees
(CXCR4* NEAR/2 receptor*) or (LESTR* NEAR/2 receptor*)
fusin*
CXC NEAR/2 receptor*
leukocyte derived seven transmembrane domain*
CXCR4
LESTR*
CD184
plerixafor
(AMD 3100 or JM 3100)
(Mozobil* or Mobizil*)
(#28 OR #29 OR #30 OR #31 OR #32 OR #33 OR #34 OR #35 OR #36 OR #37 OR #38)
(#27 AND #39)

Appendix 2. MEDLINE search strategy

Searches
exp Lymphoma/
lymphom$.tw,kf,ot.
linfom$.tw,kf,ot.
Hematologic Neoplasms/
((hemato$ or haemato$) adj5 (malign$ or neoplas$)).tw,kf,ot.
exp Lymphoma, Non-Hodgkin/
(non-hodgkin$ or non hodgkin$ or nonhodgkin$ or no hodgkin$ or nhl).tw,kf,ot.
(lymph$ adj2 sarcom$).tw,kf,ot.
lymphosarcom$.tw,kf,ot.
((reticulum-cell$ or reticulum cell$) adj2 sarcom$).tw,kf,ot.
reticul?sarcom$.tw,kf,ot.
or/1-11
exp Hodgkin Disease/
Germinoblastom$.tw,kf,ot.
Reticulolymphosarcom$.tw,kf,ot.
Hodgkin$.tw,kf,ot.
(malignan$ adj2 (lymphogranulom$ or granulom$)).tw,kf,ot.
or/13-17
exp MULTIPLE MYELOMA/
myelom$.tw,kf,ot.
exp Plasmacytoma/
plasm?cytom$.tw,kf,ot.
plasmozytom$.tw,kf,ot.
plasm$ cell myelom$.tw,kf,ot.
myelomatosis.tw,kf,ot.
Leukemia, Plasma Cell/
(plasma$ adj3 neoplas$).tw,kf,ot.
kahler.tw,kf,ot.
or/19-28
12 or 18 or 29
Receptors, CXCR4/
((CXCR4$ or LESTR$) adj2 receptor$).tw,kf,nm,ot.
fusin$.tw,kf,nm,ot.
(CXC adj2 receptor$).tw,kf,ot.
leukocyte derived seven transmembrane domain$.tw,kf,nm,ot.
CXCR4.tw,kf,nm,ot.
LESTR$.tw,kf,ot.
CD184.tw,kf,nm,ot.
plerixafor.tw,kf,ot.
(AMD 3100 or JM 3100).tw,kf,nm,ot.
(Mozobil$ or Mobizil$).tw,kf,ot.
or/31-41
30 and 42
randomized controlled trial.pt.
controlled clinical trial.pt.
randomized.ab.
placebo.ab.
drug therapy.fs.
randomly.ab.
trial.ab.
groups.ab.
or/44-51
humans.sh.
52 and 53
43 and 54

Contributions of authors

Tim Hartmann: Protocol development

Kai Hübel: Clinical expertise

Ina Monsef: Search strategy

Andreas Engert: Clinical expertise

Nicole Skoetz: Protocol development, methodological expertise

Declarations of interest

None known.

Sources of support

Internal sources

  • University Hospital of Cologne, Germany.

    Department I of Internal Medicine

External sources

  • No sources of support supplied

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