Granulopoiesis-stimulating factors for preventing infections after autologous peripheral stem cell transplantation for lymphoma and multiple myeloma in adults

  • Protocol
  • Intervention

Authors


Abstract

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

The aim of the present review to summarise the current evidence for the role of rhG-CSF, PEG-filgrastim and bio-similar G-CSFs compared with placebo or no granulopoietic CSF administration after HDT and ASCT for HL, NHL and MM.

Background

Description of the condition

According to the Norton-Simon-hypothesis, cancer resistance can result from a reduced sensitivity of tumour cells to chemotherapeutic agents (Norton 1982). Therefore, intensification of chemotherapy by increasing chemotherapy doses should result in higher cure rates. However, historically, in haematologic neoplastic diseases (cancers of the blood) specifically, until the development of autologous stem cell transplantation (ASCT) intensification with high dose chemotherapy (HDT) was precluded by chemotherapy-induced severe bone marrow toxicity (Gorin 1992). ASCT is the transplantation of a special type of marrow or peripheral cell, called stem cells, which are a source of self-renewing cells capable of differentiating into blood cells of all lineages and giving rise to erythrocytes (red blood cells), white blood cells and thrombocytes (cells involved in clotting). Following collection from a patient, stem cells can be safely cryopreserved (stored at a very low temperature) for subsequent use in the same patient (autologous transplantation) as a source of haematopoietic rescue (blood renewal) after high dose therapy (HDT). Haematopoietic stem cells for autologous transplantation can be collected from either the bone marrow (Gorin 1992; Philip 1995), or from peripheral blood following mobilisation from the bone marrow (Sheridan 1992). Autologous peripheral blood stem cell transplantation (ASCT) is currently preferred to autologous bone marrow stem cell transplantation (ABMT) because it achieves more rapid regrowth of red blood cells, white blood cells and platelets (Ottinger 1996; Vallenga 2001; Vose 2002).

HDT followed by ASCT has been successfully incorporated into the treatment of lymphoma (Yuen 1997; Sebban 2008; Le Gouill 2011), and multiple myeloma (MM) (Barlogie 2010). Lymphomas are a heterogeneous group of malignancies of the lymphatic system, classified into two categories: Hodgkin's lymphoma (HL) and non-Hodgkin's lymphoma (NHL) (Freedman 1999). HL accounts for approximately 10% of all lymphomas and approximately 0.6% of all cancers diagnosed annually in the developed world (Jemal 2009). This amounts to approximately 8830 new cases, and about 1300 deaths in the USA annually (Siegel 2011). The incidence of HL in Europe is approximately 2.4 cases per 100,000 persons (Sant 2010). Mortality from HL declined between the 1970s and 1990s in the USA and Western Europe, with resulting mortality rates of 0.5 per 100,000 in men and 0.3 per 100,000 in women (Levi 2002). The high success rates in HL treatment have been attributed to the development of multi-agent chemotherapy and the refinement of radiotherapy (Kennedy 1985). Relapse rates after first-line therapy range from 10% to 15% in favourable prognosis stage I-II disease (Specht 1998), to 30% to 40% in advanced disease (Somers 1994). HDT followed by ASCT is currently considered to be the treatment of choice for the following subsets of relapsed patients with HL: early relapse (i.e. within a year of treatment) and late relapse (i.e. more than 12 months after treatment), or after failure of initial chemotherapy; and second relapse after conventional treatment for first relapse (Brice 2008).

NHL is a heterogeneous (variable) group of lymphoproliferative disease variously derived from the clonal expansion of B-cell lymphocytes, T-cell lymphocytes, natural killer (NK)-cells or precursors of these cells. According to the World Health Organization (WHO) classification, NHL comprise the following subtypes: follicular lymphoma (FL); diffuse large B-cell lymphoma (DLBCL), Burkitt's lymphoma; mantle cell lymphoma; mucosa-associated lymphoid tissue (MALT) lymphoma; mature T-cell lymphoma; chronic lymphocytic lymphoma (CLL/SLL), mediastinal large B-cell lymphoma, anaplastic large-cell lymphoma; nodal marginal zone lymphoma, and precursor T-lymphoblastic lymphoma, lymphoplasmacytic lymphoma, and other types (Jaffe 2001). The most common subtypes of NHL are DLBCL and FL, accounting respectively for approximately 30% and 20% of patients with NHL (Glass 1997).The most relevant feature of NHL is its increase in incidence over the last 20 years in both the USA and Europe, with an overall annual incidence rate of 19.0 cases per 100,000 persons in 2001 (Ries 2004). It is estimated that between 1997 and 2001 the NHL mortality rate in the USA ran at 8.4 deaths per 100,000 (Ries 2004). However, survival rates differ according to histologic subtype (cell type), with high grade lymphomas - such as Burkitt's lymphoma, immunoblastic lymphoma and central nervous system lymphoma having the poorest survival rates (Sherr 1996; National Cancer Institute 2005).

HDT followed by ASCT has been incorporated into the treatment of NHL for both newly diagnosed and relapsing patients (Ketterer 1997), depending on histologic subtype. In patients with relapsed or refractory DLBCL that responds to a second course of chemotherapy, HDT followed by ABMT results in superior overall survival rates than chemotherapy alone (Philip 1995). In patients with FL, HDT followed by ASCT prolongs progression-free survival and overall survival rates in those who are in complete remission, or have minimal disease at the time of HDT (Sebban 2008). MM is characterised by the neoplastic (cancerous) proliferation of a single clone of plasma cells (i.e. monoclonal immunoglobulin). This clone of plasma cells proliferates in the bone marrow and often results in extensive skeletal destruction, reduced bone mass and pathologic fractures (Kyle 2003). The median age at diagnosis is 66 years; only 10% of patients are under 50 years of age and only 2% are under 40 years (Kyle 2003). MM accounts for approximately 1% of all cancers and slightly more than 10% percent of haematologic malignancies in the USA. The annual incidence in the USA is approximately four to five per 100,000. A similar incidence has been reported in the South Thames area of the United Kingdom and in Europe in general (Phekoo 2004). A high dose of the anti-cancer drug melphalan followed by ASCT, performed either at the time of initial diagnosis or at relapse, is considered to be the best treatment for younger patients (i.e. under 70 years of age) with newly diagnosed MM (Moreau 2002; Child 2003; Palumbo 2004).

Description of the intervention

Granulocytes are a type of white blood cell characterized by the presence of granules in their cytoplasm. The most abundant of the granulocytes are neutrophils. Granulocytes are derived from stem cells residing in the bone marrow and the differentiation of these stem cells from pluripotent (i.e. cells that can develop into many cell types) haematopoietic stem cells into granulocytes is termed granulopoiesis. Granulocyte colony-stimulating factor (G-CSF) is a glycoprotein, growth factor and cytokine produced by a number of different tissues to stimulate the bone marrow to produce granulocytes and stem cells. G-CSF also stimulates the survival, proliferation, differentiation, and function of neutrophil precursors and mature neutrophils (Kauschansky 2006). The artificially produced recombinant human G-CSF, synthesised in an Escherichia coli expression system, is called filgrastim. Filgrastim (Neupogen®) and PEG (polyethylene glycol)-filgrastim (Neulasta®) are two commercially available forms of recombinant human G-CSF (rhG-CSF). The PEG form is a recombinant methionyl form of human G-CSF, in which a 20 kDa polyethylene glycol molecule has been covalently bound to the N-terminal methionine residue. It has a much longer half-life (time during which the medicine can act within the body), reducing the necessity for daily injections. A single fixed dose of PEG-filgrastim can be given once during each chemotherapy cycle in conjunction with a variety of chemotherapy regimens (Yang 2011). The recent expiry of the patent for filgrastim allowed the marketing of generic versions, called bio-similars, which are drugs that are similar, but not identical, to the original drug (Zuniga 2010). Approved bio-similar G-CSFs include Biograstim®, Filgrastim ratiopharm/Ratiograstim® (this drug was withdrawn from use in 2011), Tevagrastim®, Zarzio® and Nivestim® (Gascon 2012). Another form of recombinant human G-CSF called lenograstim (Myelostim®, Granocyte®) is synthesised in Chinese hamster ovary cells. No clinical or therapeutic consequences of the differences between filgrastim and lenograstim have yet been identified, but there are no formal comparative studies. In adults, the recommended dose of rhG-CSF is 5 µg/kg/day. The usual route for drug administration is subcutaneous injection. G-CSFs are generally well tolerated, though bone pain, flu-like symptoms including fever, flushing, malaise, myalgia (muscle pain), arthralgia (joint pain), anorexia (lack of appetite), and headache, as well as mild elevation of aminotransferases and rashes have been reported. These side-effects are transitory and are alleviated by antipyretics drugs that reduce fever (Metcalf 2010).

How the intervention might work

Despite the faster repopulation of bone marrow obtained from reinfusion using peripheral stem cell transplantation(SCT), patients treated with HDT followed by ASCT are still susceptible to infections and sepsis because of a residual period of neutropenia - a condition that lasts seven to 10 days after peripheral SCT in which the neutrophil count falls below 1000/µl. The incidence of fever associated with neutropenia (i.e. febrile neutropenia) in this setting ranges from 60% to 100% of treated patients, with the majority of fevers classified as being of unknown origin (Reich 2005; Gil 2007). Moreover, the duration of severe neutropenia, in which the neutrophil count falls below 500/µl, following HDT and ASCT is correlated with the development of infectious complications that have a major impact on overall morbidity and mortality (Freifeld 2011). G-CSFs could be able to shorten the period of neutropenia following HDT and ASCT by stimulating production of neutrophils, and thus reduce the incidence of febrile neutropenia and infections. The faster speed of neutrophil recovery associated with G-CSF administration could eventually reduce the mortality associated with ASCT.

Why it is important to do this review

The prophylactic use of G-CSF in patients with malignant lymphoma undergoing conventional chemotherapy has been shown to reduce the risk of certain adverse events, including severe neutropenia, febrile neutropenia and infections. Despite this, the addition of G-CSF failed to improve overall survival (OS) or freedom from treatment failure (FFTF) in comparison with no prophylaxis (Bohlius 2008). Moreover, another recent Cochrane review investigating the role of colony-stimulating factors for the prevention and treatment of infectious episodes in patients with acute myelogenous leukaemia failed to demonstrate any advantage for infection-related outcomes (Gurion 2011). Contrary to its efficacy in the setting of ABMT (Advani 1992; Gorin 1992), the value of G-CSF following ASCT is less well defined and no overall consensus exists about its optimal use. However, despite the fact that the addition of G-CSF may accelerate neutrophil recovery in the setting of ASCT (Spitzer 1994; Demirer 2002), no clear demonstration of the related clinical benefit is available.This review will clarify the efficacy of G-CSFs in relation to various clinical issues following HDT and ASCT, and provide the basis of a more evidence-informed use of these growth factors.

Objectives

The aim of the present review to summarise the current evidence for the role of rhG-CSF, PEG-filgrastim and bio-similar G-CSFs compared with placebo or no granulopoietic CSF administration after HDT and ASCT for HL, NHL and MM.

Methods

Criteria for considering studies for this review

Types of studies

RCTs, including full-text and abstract publications and unpublished data, but excluding quasi-randomised trials and cross-over trials.

Types of participants

Adult patients 16 years of age and over with HL, NHL, and MM undergoing autologous peripheral stem cell transplantation as first or subsequent line of therapy. Patients with HIV infection will be excluded.

Types of interventions

Experimental intervention
  • Administration of granulopoiesis stimulating factors, i.e. G-CSF, granulocyte macrophage colony-stimulating factor (GM-CSF), and PEG-G-CSF, or bio-similar G-CSFs after autologous peripheral stem cell transplantation.

Control intervention
  • Placebo after autologous peripheral stem cell transplantation.

  • No granulopoiesis stimulating factors after ASCT.

Participants in both groups should receive equal additional treatments, e.g. antibiotic, antifungal and antiviral prophylaxis and identical care. We will allow supportive care that follows a fixed schedule or is given as required.

Types of outcome measures

Primary outcomes
  • Number of infectious disease episodes (incidence). Infections will be defined on the basis of their description in the primary studies. In case of different definitions we will perform sensitivity analyses.

  • Number of febrile neutropenia episodes defined as an absolute neutrophil count (ANC) of less than 500/µl or less than 1000/µl and predicted to fail below 500 µl within 48 hours with fever or clinical signs of sepsis (Freifeld 2011).

  • Infection-related mortality.

Secondary outcomes
  • Time to neutrophil count recovery. We will consider the number of days needed for the ANC to rise from less than 500/µl to 500/µl.

  • Number of grade 3 to 4 infectious disease episodes (incidence).

  • Length of hospitalisation (to reduce bias we will consider days of hospitalisation only if a discharge protocol is provided by the authors; in case of different definitions we will perform sensitivity analyses).

  • Use of intravenous antibiotic therapy.

  • Use of empiric antifungal therapy.

  • Number of red blood cell transfusions.

  • Number of platelet transfusions.

  • Severe adverse events (bone pain, splenomegaly (enlargement of the spleen), hyperleukocytosis (excessive levels of white blood cells in the blood), myocardial ischaemia (reduced blood supply to the heart) WHO grade III-IV).

  • Overall survival.

  • Quality of life.

Search methods for identification of studies

We will search databases and registers of clinical trials and handsearch relevant journals, conference proceedings and bibliographies from retrieved trials, meta-analyses and narrative reviews. We will contact drug companies and authors of eligible trials for further details. We will search from 1992 onwards, as this is the year that autologous peripheral stem cell transplantation was introduced to clinical practice.

Electronic searches

We will adopt search strategies from those suggested in Chapter 6 of the Cochrane Handbook for Systematic Reviews of Interventions (Lefebvre 2011). These are provided in Appendix 1 and Appendix 2. To reduce the potential for language bias, we will apply no restrictions regarding language of publication.

The following electronic databases will be searched from 1992 onwards.

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

  • MEDLINE (1992 to present) (Appendix 2).

We will also search the metaRegister of controlled trials: http://www.controlled-trials.com/mrct/ for ongoing trials.

Searching other resources

We will search the conference proceedings of annual meetings for the following societies - that are not included in CENTRAL - for abstracts.

  • European Society of Medical Oncology (ESMO) (2000 to present).

  • ISHL (International Symposium on Hodgkin Lymphoma) (2000 to present)

We will handsearch the reference sections of all identified trials, relevant review articles and current treatment guidelines.

We will search the following information sources for unpublished studies and grey literature.

  • The System for Information on Grey Literature in Europe (SIGLE) database.

Where deemed necessary, we will contact manufacturers of commercially-available granulocyte stimulating factors, and principal clinical investigators to retrieve unpublished papers.

Data collection and analysis

Selection of studies

Following the literature search process and after merging search results using reference management software, AB and EM will examine titles and abstracts independently. AB and EM will classify trials independently as eligible or ineligible for inclusion, using an eligibility form concerned with study design and compliance with inclusion criteria (Higgins 2011a). We will actively seek and exclude duplicate records (i.e. all relevant papers will be checked for data, but if more than one paper has been written about a particular trial the population will only entered into the analysis once).

Where there is doubt, we will include full text analysis and discuss eligibility with review authors to finalise a decision (preferably including studies rather than losing relevant data). We will use a PRISMA flow-diagram to show numbers of records and articles identified, excluded and included (Liberati 2009).

Data from abstracts will be extracted if a judgement of study quality is possible (e.g. with regard to randomisation methods).

Data extraction and management

Two review authors will extract data independently according to the recommendations in Chapter 7 of the Cochrane Handbook for Systematic Reviews of Interventions (Higgins 2011a), by using a standardised data extraction form containing the following items:

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

  • Quality assessments: sequence generation, allocation concealment, blinding (for participants, personnel, and outcome assessors), incomplete outcome data, selective outcome reporting, intention-to-treat analysis (ITT), and other sources of bias.

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

  • Participant characteristics: age, gender, ethnicity, number of participants recruited, allocated and evaluated; participants lost to follow-up, stage of disease, histological subtype, and additional diagnoses.

  • Interventions: setting, type, dosage, schedule and formulation of granulopoietic CSFs; type and intensity of pre-treatment (chemotherapy regimen, radiotherapy, duration of follow-up, and number of peripheral stem cells re-infused.

  • Outcomes: number of infectious disease episodes, number of febrile neutropenia episodes, days of hospitalisation, use of intravenous antibiotic therapy, use of empirical antifungal therapy, number of platelet transfusions, overall survival, infection-related mortality, and severe adverse events.

Assessment of risk of bias in included studies

To assess the methodological quality and the risk of bias in included studies, two review authors will independently collect information about the methods employed in the studies. For each study we will create a 'Risk of bias' table with the domain, support for judgement, and review authors' judgement for each domain according to the recommendations in Chapter 8 of the Cochrane Handbook for Systematic Reviews of Interventions (Higgins 2011b). Each domain will be assessed using the Cochrane criteria for judgement of bias, for each eligible study.

The risk of bias in each domain will be assessed and categorized into:

  • low risk of bias, plausible bias unlikely to seriously alter the results;

  • high risk of bias, plausible bias that seriously weakens confidence in the results; and

  • unclear risk of bias, plausible bias that raises some doubt about the results.

We will resolve disagreements between review authors by discussion with a third review author until consensus is obtained. The domains for assessment will be:

  • sequence generation;

  • allocation concealment;

  • blinding (participants, personnel, and outcome assessors);

  • incomplete outcome data;

  • selective outcome reporting;

  • ITT analysis;

  • other sources of bias.

Measures of treatment effect

For all binary outcomes, we will extract the number of events and participants in both the control and experimental arm(s) from each study. The relative risk (RRs) will be calculated with their 95% CI using the inverse variance method.

For each trial the hazard ratio (HR) will be estimated; the method used to do this will depend upon the data provided in the publications. The most accurate method consists of calculating the estimated HR and its standard error using two of the following parameters: the CIs for the HR, the log rank statistics, its P value or the O-E statistic. If these data are not available, we will look at the total number of events, or the number of participants at risk in each arm. Finally, if the only available data are in the form of graphical presentation of survival distributions, we will extract survival rates at some specified time in order to reconstruct the HR estimate and its variance, with the assumption that the rate of patients censored was constant during the study follow-up (Parmar 1998; Tierney 2007). The individual HR estimates will be combined into an overall HR through the inverse variance method using log (HR) and its standard error, so that we can perform a random-effects analysis.

For continuous data, such as quality of life, we will compare means and standard errors.

Unit of analysis issues

We will calculate the logarithms of the rate ratios of each trial and combine them using the generic inverse variance method (Hasselblad 1995). Whenever necessary we will calculate an approximate standard error of the log rate ratio given by √ (1/A+1/C) where A represents the observed number of events in the experimental group, and C represents the observed number of events in the control group.

Dealing with missing data

As suggested in Chapter 16 of the Cochrane Handbook for Systematic Reviews of Interventions (Higgins 2011c), there are many potential sources of missing data that need to be taken into account at study level, outcome level, summary data level, individual level and characteristics of study level (e.g. for subgroup analysis). Firstly, it is important to distinguish between those data that are missing at random and those that are not missing at random.

We will contact the original investigators to request missing data. After this, if data are still missing, we will make explicit assumptions for methods we will use; for example that the data are missing at random, or that missing values have a particular value, such as a poor outcome. Sensitivity analyses will be performed according to the worst/best case scenario.

Assessment of heterogeneity

Statistical analysis of heterogeneity will be performed using the Chi ² test with a significance level set at P value less than 0.1. We will calculate the percentage of the variability in the effect estimates using using the I² statistic (moderate heterogeneity will be indicated when I² exceeds 30% and considerable heterogeneity will be indicated when I² exceeds 75% (Deeks 2011). We will explore potential causes of heterogeneity by sensitivity analysis subgroup analysis and meta-regression-the latter only if appropriate.

Assessment of reporting biases

We will perform searches for unpublished studies, and, if at least 10 studies are included in the meta-analysis, consider constructing a funnel plot for the primary endpoint (Sterne 2011).

Data synthesis

We will perform analyses according to the recommendations in Chapter 9 of the Cochrane Handbook for Systematic Reviews of Interventions (Deeks 2011). We will use aggregated data for analysis. For statistical analysis, we will enter data into the Cochrane review-writing package, Review Manager (RevMan 5.1). One review author will input data into the software and a second review author will check them for accuracy. As we expect moderate heterogeneity among the included studies, we will perform meta-analyses using a random-effects model for all comparisons. If appropriate, we will calculate the number needed to treat for an additional beneficial outcome and the number needed to treat for an additional harmful outcome.

In addition, we will create 'Summary of findings' tables using the GRADE profiler.

Subgroup analysis and investigation of heterogeneity

Heterogeneity will be examined using the following subgroups.

  • Trials based on different types of granulopoiesis-stimulating factors.

  • Trials based on different timing or doses of administration of granulopoiesis-stimulating factors.

  • Trials based on lymphoma patients versus trials based on myeloma patients.

  • Trials based on newly-diagnosed patients versus trials based on relapsed patients.

Sensitivity analysis

Sensitivity analysis will be performed to examine the influence of the following factors

  • Placebo-controlled studies versus open-label studies.

  • Concealment of allocation.

  • Size of studies (fewer than 100 patients versus a minimum of 100 patients).

  • Published versus unpublished, unreported or abstract-based data.

  • Duration of follow-up.

  • Random-effects versus fixed-effect modelling.

  • ITT analysis with imputed missing data according to best-case/worst-case scenario for the different treatment groups in every trial.

  • Exclusion of studies with outlying results.

  • Studies with different definitions of infection.

Acknowledgements

We are grateful to Mrs Sabine Kluge (Managing Editor) for her invaluable support in writing the protocol.

Appendices

Appendix 1. CENTRAL search strategy

1exp LYMPHOMA/
2HEMATOLOGIC NEOPLASMS/
3(lympho* adj2 (neoplasm* or malign* or tumo?r* or sarcom*)).tw,kf,ot.
4(lympha* adj2 (neoplasm* or malign* or tumo?r* or sarcom*)).tw,kf,ot.
5(hemato$ adj (malign$ or neoplas$)).tw,kf,ot.
6(haemato$ adj (malign$ or neoplas$)).tw,kf,ot.
7HODGKIN DISEASE/
8hodgkin*.tw,kf,ot.
9Germinoblastom*.tw,kf,ot.
10Reticulolymphosarcom*.tw,kf,ot.
11(malignan* adj2 (lymphogranulom* or granulom*)).tw,kf,ot.
12LYMPHOMA, NON-HODGKIN/
13histiocy*.tw,kf,ot.
14(nonhodgkin* or non-hodgkin*).tw,kf,ot.
15mycos* fungo*.tw,kf,ot.
16sezary.tw,kf,ot.
17granulom*.ti.
18burkit*.tw,kf,ot.
19lymphosarcom*.tw.
20reticulosarcom*.tw,kf,ot.
21reticulum-cell sarcom*.tw,kf,ot.
22or/1-21 search part Lymphoma
23exp MULTIPLE MYELOMA/
24myelom$.tw,kf,ot.
25exp PLASMACYTOMA/
26plasm?cytom$.tw,kf,ot.
27plasmozytom$.tw,kf,ot.
28plasm$ cell myelom$.tw,kf,ot.
29myelomatosis.tw,kf,ot.
30LEUKEMIA, PLASMA CELL/
31(plasma$ adj3 neoplas$).tw,kf,ot.
32kahler.tw,kf,ot.
33or/23-32 search part Multiple Myeloma
3422 or 33 search part disease
35COLONY-STIMULATING FACTORS/
36exp COLONY-STIMULATING FACTORS, RECOMBINANT/
37exp GRANULOCYTE COLONY STIMULATING FACTOR, RECOMBINANT/
38exp GRANULOCYTE COLONY-STIMULATING FACTOR/
39exp GRANULOCYTE-MACROPHAGE COLONY-STIMULATING FACTOR/
40MACROPHAGE COLONY-STIMULATING FACTOR/
41(RHG?CSF$ or RH-G?CSF$ or RHGM?CSF$ or RH-GM?CSF$).tw.
42(RMETHUG$ or RHMETHUG$ or R-METHUG$ or RH-METHUG$).tw.
43(RHUG$ or RHUGM$).tw.
44(GCSF$ or G-CSF$).tw.
45(GM-CSF$ or GMCSF$).tw.
46(GRANULO?YT$ adj3 FA#TOR$).tw.
47(MA#ROPHAG$ adj5 FA#TOR$).tw.
48FILGRASTIM$.tw,hw,nm,kf.
49neupogen$.tw,hw,nm,kf.
50religrast$.tw,kf,nm,kf.
51nugraf$.tw,kf,nm,kf.
52LENOGRASTIM$.tw,hw,nm,kf.
53Granocyte.tw,hw,nm,kf.
54Euprotin.tw,hw,nm,kf.
55PEG?FILGRASTIM$.tw,hw,nm,kf.
56Neulasta.tw,hw,nm,kf.
57LEUKINE.tw,hw,nm,kf.
58sagramostim$.tw,kf,nm,ot.
59MOLGRAMOSTIN$.tw,hw,nm,kf.
60macrogen$.tw,kf,nm,ot.
61Mielogen$.tw,kf,nm,ot.
62Leucomax$.tw,hw,nm,kf.
63nartograstim$.tw,kf,nm,ot.
64pegnartograstim$.tw,kf,nm,ot.
65ecogramostim$.tw,kf,nm,ot.
66regramostim$.tw,kf,nm,ot.
67leridistim$.tw,kf,ot.
68or/35-67 search part treatment
6934 and 68 combination of disease and treatment
70autologous stem cell transplantation
71autologous hematopoietic stem cell transplantation
72autologous peripheral blood stem cell transplantation
73or/70-72 and 68 and 73 combination of disease and treatment
74and 73 combination of disease and treatment

Appendix 2. MEDLINE search strategy

1exp LYMPHOMA/
2HEMATOLOGIC NEOPLASMS/
3(lympho* adj2 (neoplasm* or malign* or tumo?r* or sarcom*)).tw,kf,ot.
4(lympha* adj2 (neoplasm* or malign* or tumo?r* or sarcom*)).tw,kf,ot.
5(hemato$ adj (malign$ or neoplas$)).tw,kf,ot.
6(haemato$ adj (malign$ or neoplas$)).tw,kf,ot.
7HODGKIN DISEASE/
8hodgkin*.tw,kf,ot.
9Germinoblastom*.tw,kf,ot.
10Reticulolymphosarcom*.tw,kf,ot.
11(malignan* adj2 (lymphogranulom* or granulom*)).tw,kf,ot.
12LYMPHOMA, NON-HODGKIN/
13histiocy*.tw,kf,ot.
14(nonhodgkin* or non-hodgkin*).tw,kf,ot.
15mycos* fungo*.tw,kf,ot.
16sezary.tw,kf,ot.
17granulom*.ti.
18burkit*.tw,kf,ot.
19lymphosarcom*.tw.
20reticulosarcom*.tw,kf,ot.
21reticulum-cell sarcom*.tw,kf,ot.
22or/1-21 search part Lymphoma
23exp MULTIPLE MYELOMA/
24myelom$.tw,kf,ot.
25exp PLASMACYTOMA/
26plasm?cytom$.tw,kf,ot.
27plasmozytom$.tw,kf,ot.
28plasm$ cell myelom$.tw,kf,ot.
29myelomatosis.tw,kf,ot.
30LEUKEMIA, PLASMA CELL/
31(plasma$ adj3 neoplas$).tw,kf,ot.
32kahler.tw,kf,ot.
33or/23-32 search part Multiple Myeloma
3422 or 33 search part disease
35COLONY-STIMULATING FACTORS/
36exp COLONY-STIMULATING FACTORS, RECOMBINANT/
37exp GRANULOCYTE COLONY STIMULATING FACTOR, RECOMBINANT/
38exp GRANULOCYTE COLONY-STIMULATING FACTOR/
39exp GRANULOCYTE-MACROPHAGE COLONY-STIMULATING FACTOR/
40MACROPHAGE COLONY-STIMULATING FACTOR/
41(RHG?CSF$ or RH-G?CSF$ or RHGM?CSF$ or RH-GM?CSF$).tw.
42(RMETHUG$ or RHMETHUG$ or R-METHUG$ or RH-METHUG$).tw.
43(RHUG$ or RHUGM$).tw.
44(GCSF$ or G-CSF$).tw.
45(GM-CSF$ or GMCSF$).tw.
46(GRANULO?YT$ adj3 FA#TOR$).tw.
47(MA#ROPHAG$ adj5 FA#TOR$).tw.
48FILGRASTIM$.tw,hw,nm,kf.
49neupogen$.tw,hw,nm,kf.
50religrast$.tw,kf,nm,kf.
51nugraf$.tw,kf,nm,kf.
52LENOGRASTIM$.tw,hw,nm,kf.
53Granocyte.tw,hw,nm,kf.
54Euprotin.tw,hw,nm,kf.
55PEG?FILGRASTIM$.tw,hw,nm,kf.
56Neulasta.tw,hw,nm,kf.
57LEUKINE.tw,hw,nm,kf.
58sagramostim$.tw,kf,nm,ot.
59MOLGRAMOSTIN$.tw,hw,nm,kf.
60macrogen$.tw,kf,nm,ot.
61Mielogen$.tw,kf,nm,ot.
62Leucomax$.tw,hw,nm,kf.
63nartograstim$.tw,kf,nm,ot.
64pegnartograstim$.tw,kf,nm,ot.
65ecogramostim$.tw,kf,nm,ot.
66regramostim$.tw,kf,nm,ot.
67leridistim$.tw,kf,ot.
68or/35-67 search part treatment
6934 and 68 combination of disease and treatment
70autologous stem cell transplantation
71autologous hematopoietic stem cell transplantation
72autologous peripheral blood stem cell transplantation
73or/70-72
74randomized controlled trial.pt.
75controlled clinical trial.pt.
76randomized.ab.
77placebo.ab.
78drug therapy.fs.
79randomly.ab.
80trial.ab.
81groups.ab.
82or/74-81
83humans.sh.
8482 and 83 Cochrane RCT-Filter
8534 and 68 and 73 and 84 combination of disease, treatment and RCT-Filter

Contributions of authors

AB and MC wrote the protocol.

AB will be the guarantor of the review, and will be responsible for designing the search strategy, undertaking searches, writing to authors of papers for additional information, providing additional data about papers, obtaining and screening data on unpublished studies, and providing general advice for the review. Previous work by AB provides the foundation of the current review.

AB and FA will be responsible for data collection, screening search results, organising retrieval of papers, screening retrieved papers against eligibility criteria, appraising quality of papers, and extracting data from papers.

IM will be responsible for appraising quality of papers.

MM will be responsible for entering data into RevMan.

MC will be responsible for statistical analysis.

AB, EM, MC and IM will be responsible for interpretation of data, and for providing a methodological, clinical, policy and consumer-oriented perspective.

Declarations of interest

Atto Billio: no interests to declare.

Enrico Morello: no interests to declare.

Michael Mian: no interests to declare.

Francesca Antoniazzi: no interests to declare.

Ivan Moschetti: no interests to declare.

Michela Cinquini: no interests to declare.

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