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Interleukin‐2 as maintenance therapy for children and adults with acute myeloid leukaemia in first complete remission

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Abstract

This is a protocol for a Cochrane Review (Intervention). The objectives are as follows:

The primary objective of this study will be to evaluate the efficacy of interleukin‐2 (IL‐2) as maintenance therapy in patients with acute myeloid leukaemia (AML) who have achieved first complete remission (CR).

Background

Description of the condition

Acute myeloid leukaemia (AML) is a malignant cancer of haematopoietic stem cells characterised by the rapid growth of non‐functional myeloblasts in the bone marrow and interference with the production of normal blood cells. The symptoms of AML relate to the replacement of normal bone marrow with leukaemic cells, which will lead to functional pancytopenia, with the symptoms of anaemia, neutropenia and thrombocytopenia (Lowenberg 1999). AML is a relatively uncommon cancer, with an estimated incidence of 3.5/100,000 people, a rate that has remained stable during recent decades (SEER 2010). The incidence of AML increases with age;people over 60 years make up a large proportion of those with this disease and their survival time is only half of that of younger patients (Buchner 2009).

There are two commonly used classifications for AML: the French‐American‐British (FAB) system and the World Health Organization (WHO) system. The former classification system was introduced in 1976 and uses morphological and cytochemical methods; it subcategorises AML into eight subtypes, from M0 through to M7. It sets the threshold between high‐grade myelodysplastic syndromes and AML ≧ 30% blasts (Bennett 1976). The WHO classification system was introduced in 1999 and revised in 2008. It is based on morphology and newer prognostic factors to define different entities. It subcategories AML into 17 subtypes and lowers the threshold to > 20% blasts in diagnosis (Harris 1999; Vardiman 2009).

Normally, the treatment of AML consists of two well validated treatment phases: the remission induction phase; and the consolidation (post‐remission) phase. The remission induction phase aims to achieve a rapid, complete remission (CR) and consolidation (post‐remission) phase to achieve a durable molecular remission. Possibilities for consolidation are autologous stem cell transplantation and allogenic stem cell transplantation, as well as chemotherapy (Heitger 2002). Many prognostic factors are responsible for the predictors of treatment response and overall survival of AML (for example, the patients' age, performance status, karyotype and cytological AML subtype are all important predictors of treatment outcome) (Appelbaum 2006; Frohling 2006; Juliusson 2009; Wheatley 2009).

Description of the intervention

AML patients who achieve CR and subsequently relapse have a poor survival prospect (Rowe 2005). Maintenance therapy, following the consolidation period is needed in AML treatment, as it aims to maintain patients in first CR and prevent relapse (Krug 2010). Maintenance therapy is not an integral part of the standard treatment for AML. The effect of interleukin‐2 (IL‐2) as remission maintenance treatment in AML patients remains controversial. Case reports and previous small clinical trials showed that IL‐2 induced prolonged remissions and may have brought a modest benefit to AML patients in first CR for remission maintenance (Farag 2002; Maraninchi 1991; Meloni 1994; Stein 2002). A series of randomised controlled trials (RCTs) followed that demonstrated the putative benefits of IL‐2 in survival outcomes in AML patients (Baer 2008; Blaise 2000; Kolitz 2007; Lange 2008; Pautas 2010). Their results all revealed a trend in favour of IL‐2 maintenance treatment, with higher disease‐free survival and overall survival rates. The Kolitz 2007 trial (which evaluated the efficacy of IL‐2 in 214 patients with AML in first CR after completing all planned chemotherapy), however, showed no significant difference between the IL‐2 treatment group and the no treatment group in terms of the three‐year disease‐free survival rate (56% versus 45%; P = 0.11) and three‐year overall survival rate (68% versus 61%; P=0.09). Buyse 2011 conducted an individual patient data meta‐analysis and they concluded that IL‐2 alone as a remission maintenance therapy was not effective for AML patients in first CR. Only the result of a randomised phase 3 trial with 320 AML patients in CR indicates that IL‐2 in combination with histamine dihydrochloride provides an efficacious treatment and can significantly reduce the relapse risk (Brune M 2006).

In addition to serving as maintenance therapy, the potential role of low‐dose IL‐2 as part of the consolidation immunotherapy for the maintenance of CR in AML is obvious, particularly to patients in CR with a low or minimal burden of leukaemia (Thoren 2009).

How the intervention might work

IL‐2 is a strongly immune‐stimulatory cytokine, which significantly promotes the proliferation of T‐lymphocytes responsible for tumour specific cytotoxic function, and augments the cytotoxic effect of natural killer cells (T‐ and NK‐cells) (Lauria 1994), suggesting that IL‐2 is a potential candidate for leukaemia therapy by its cytotoxic lymphocytes pathway. Previous preclinical studies proved that IL‐2 alone was effective in treating leukaemia of animal models (Fierro 1988; Johnson 1989). A few non‐randomised trials also reported that IL‐2 contributed to achieving objective remissions in patients treated with high doses (Maraninchi 1991; Maraninchi 1998). IL‐2 can also replicate the beneficial effects of allogeneic haematopoietic stem cell transplantation to prevent leukaemic relapse. However, IL‐2 treatment in high doses had too many adverse effects including fever, flushing, vomiting, diarrhea, fatigue, thrombocytopenia, renal dysfunction, and pulmonary oedema (Lauria 1994; Stoppa 1991; Tajima 1996).

Low‐dose IL‐2 therapy was then considered for leukaemic maintenance therapy . Treatment with low‐dose IL‐2 which saturate only high affinity IL‐2 receptors can result in a selective expansion of a subset of NK cells, especially CD56bright and CD16di(Caligiuri 1993). In addition, the effect of antigen‐independent cytotoxicity against NK cell‐resistant AML blasts would also achieved maximal activation level when these high affinity receptors were saturated by low‐dose IL‐2. A study also demonstrated that low‐dose IL‐2 as post‐remission therapy was well tolerated when dosages were administrated to elderly patients with AML (Farag 2002).

Why it is important to do this review

To date, IL‐2 as remission maintenance therapy has been evaluated in several RCTs, which examined its putative therapeutic potential to patients with AML in first CR (Baer 2008; Blaise 2000; Kolitz 2007; Lange 2008; Pautas 2010; Willemze 2009). Given different ages, lengths of follow‐up, remission induction regimens, doses of IL‐2 and sample sizes that were used, there is no consensus on these results. We will therefore conduct a meta‐analysis to more reliably determine the efficacy of IL‐2 monotherapy or combination therapy (IL‐2 plus maintenance chemotherapy) for remission maintenance in AML patients in first CR. Given the (at best) modest benefit of IL‐2, we will also try to identify specific subgroups among whom IL‐2 is more likely to show efficacy. Although Buyse 2011 conducted an individual patient data meta‐analysis to evaluate the effect of IL‐2, they only included patients receiving IL‐2 monotherapy for remission maintenance in AML patients in first CR. Our review will provide more comprehensive evidence for the efficacy of IL‐2 as maintenance therapy by including both patients receiving IL‐2 monotherapy and patients receiving IL‐2 combination therapy.

Objectives

The primary objective of this study will be to evaluate the efficacy of interleukin‐2 (IL‐2) as maintenance therapy in patients with acute myeloid leukaemia (AML) who have achieved first complete remission (CR).

Methods

Criteria for considering studies for this review

Types of studies

  • We will consider only RCTs as primary studies in this systematic review and meta‐analysis.

  • We will exclude quasi‐randomised trials, cross‐over trials, cohort trials and case‐controlled studies. We will include both full‐text and abstract publications.

Types of participants

  • We will include acute myeloid leukaemia (AML) patients (both adults and children) who have achieved first complete remission (CR) and have not relapsed.

  • We will include studies concerning all risk groups.

    • If trials consist of patients with different haematological malignancies, we will use data from the AML subgroup.

    • If subgroup data for AML patients are not provided, after contacting the author of the trial, we will exclude the trial if less than 80% of patients have AML.

  • Furthermore, we will assess the definition of AML used by the investigators. We will evaluate effects of different definitions of AML (i.e. more than 20% blasts versus 30% or more blasts) by subgroup analyses.

Types of interventions

Any of the following comparisons will be allowed:

  • IL‐2 maintenance monotherapy (intervention) versus placebo (control) or best supportive care (control) or maintenance chemotherapy (control); and

  • IL‐2 plus maintenance chemotherapy (intervention) versus the same maintenance chemotherapy alone (control).

We will exclude studies in which patients received allogenic or autologous stem cell transplantation in the control group. Furthermore, we will assess different doses and time schedules of the IL‐2 regimen.

Types of outcome measures

Primary outcomes

  • Disease‐free survival: defined as the time from remission to leukaemic relapse or death from any cause, whichever occurred first.

  • Overall survival: defined as the time from randomisation to death from any cause.

Secondary outcomes

  • Event‐free survival: defined as the time interval from random treatment assignment or entry into study to CR achievement failure, first relapse, or death.

  • Treatment‐related mortality: defined as time from study entry to death, resulting from non‐progressive disease where induction failures, relapses, and deaths resulting from progressive disease were competing events.

  • Adverse events.

  • Quality of life.

Search methods for identification of studies

Electronic searches

We have adapted search strategies from those suggested in the Cochrane Handbook for Systematic Reviews of Interventions (Lefebvre 2011). We will not impose any language restrictions in order to reduce the language bias.

We will search the following databases of medical literature.

  1. Cochrane Central Register of Controlled Trials (CENTRAL), The Cochrane Library, latest issue (see Appendix 1 for search strategy).

  2. MEDLINE (1950 to present, see Appendix 2 for search strategy).

  3. EMBASE (1950 to present, see Appendix 3 for search strategy).

  4. LILACS (1982 to present, see Appendix 4 for search strategy).

  5. Chinese BioMedical Literature Database (CBM) (1978 to present, see Appendix 5 for search strategy).

Searching other resources

We will search the following conference proceedings from 2000 to the present, if they are not included in CENTRAL.

  1. American Society of Hematology (ASH) (2000 to 2012).

  2. American Society of Clinical Oncology (ASCO) (2000 to 2012).

  3. European Hematology Association (EHA) (2000 to 2012).

  4. European Society of Medical Oncology (ESMO).

In addition, we will search the following conference proceedings.

  1. International Society for Hematology and Stem Cells (available at: http://www.exphem.org/search) (from 1999 to present).

We will electronically search the metaRegister of Controlled Trials (available at: http://www.controlled‐trials.com/mrct/) for ongoing trials (see Appendix 6 for search strategy) and we will save the search results of each item for further screening.

We will also check the citations of included trials and major reviews for additional studies.

Data collection and analysis

Selection of studies

We will perform the selection of studies according to the guidelines in the Cochrane Handbook for Systematic Reviews of Interventions (Higgins 2011a). After the initial screening of all the titles and abstracts of the identified studies from the above sources, two review authors (CM and YH) will independently exclude all studies that are clearly ineligible. We will assess selected studies by using an eligibility form regarding study design and compliance with inclusion criteria. The forms will contain the following questions.

  • Is the study described as randomised?

  • Were the patients diagnosed with acute myeloid leukaemia?

  • Had the patients achieved first CR and not relapsed?

  • Were the patients in the intervention group treated with IL‐2?

In case of any doubt, we will include the full‐text analysis and review authors will discuss eligibility of the studies in order to finalise a decision (preferably including studies rather than losing relevant data). According to PRISMA we will use a flow diagram to show numbers of identified records, excluded articles and included studies (Moher 2009).

Data extraction and management

We will extract data from the included trials in accordance with Chapter 7 of the Cochrane Handbook for Systematic Reviews of Interventions (Higgins 2011a) by using a standardised data extraction form. Two review authors (CM, YH) will conduct the data extraction independently. Any disagreement will be resolved by consensus. If the disagreement remains unresolved, a third review author (ZY) will independently extract the data. We will enter the extracted information onto the standardised data extraction form, which contains the following items.

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

  • Quality assessment: sequence generation, allocation concealment, blinding (participants personnel outcome assessors), incomplete outcome data, selective outcome reporting, and other 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, and time point of randomisation.

  • Participant characteristics: age, gender, number of participants recruited/allocated/evaluated, and participants lost to follow‐up.

  • Interventions: setting, dose and duration of IL‐2 treatment, type of additional or comparator chemotherapy, supportive treatment, type of treatment (first‐line treatment, pretreated patients), and additional treatment.

  • Outcomes: disease‐feee survival, overall survival, event‐free survival, treatment‐related mortality, adverse events, and quality of life..

Finally, we will enter all the extracted information into the latest Cochrane Review Manager software (RevMan 2011).

Assessment of risk of bias in included studies

Two review authors (CM, ZY) will review the included studies independently according to the recommendations in Chapter 8 of the Cochrane Handbook for Systematic Reviews of Interventions (Higgins 2011b) for assessing bias for the following criteria.

  • Sequence generation

  • Allocation concealment

  • Blinding (participants, personnel, outcome assessors)

  • Incomplete outcome data

  • Selective outcome reporting

  • Other sources of bias

We will resolve any disagreement by discussion. If disagreement persists, a third review author (YH) will extract the data independently. When necessary, we will contact the authors of the studies for clarification. If this is unsuccessful, we will report the disagreements.

Measures of treatment effect

For the time‐to‐event data including disease‐free survival, event‐free survival and overall survival, we plan to extract hazard ratios (HRs) with standard errors (SEs). If hazard ratios are not reported, we will use indirect estimating methods as described in Tierney 2007. In reporting results, we will adopt the HR with 95% confidence intervals (CIs) as the measure of treatment effect for each trial.

For binary outcomes, such as relapse rate, treatment‐related mortality and adverse events, we will extract or calculate events plus the total number of participants in each arm of every study. When reporting results, we will calculate the risk ratio (RR) with 95% CIs as measures of treatment effect for each trial.

Unit of analysis issues

We have conducted a pilot search and found that published studies eligible for this review were usually individually randomised, non‐cross‐over trials, without multiple intervention groups. In addition, quasi‐randomised trials, crossover trials and cohort trials will not be included in the review. Therefore, the unit‐of‐analysis issues related to cluster‐randomised trials, cross‐over trials and multiple intervention groups seem unlikely to arise. We will try to avoid any potential unit‐of‐analysis error by extracting and analysing the data carefully according to the methods recommended in the Cochrane Handbook for Systematic Reviews of Interventions (Higgins 2011c).

Dealing with missing data

As suggested in Chapter 16 of the Cochrane Handbook for Systematic Reviews of Interventions (Higgins 2011d), there are many potential sources of missing data: at study level; at outcome level; at summary data level; at individual level; and at study‐characteristics level (e.g. for subgroup analysis). We will seek missing data from the study authors to obtain the information which is not reported in the publications.

Moreover, it is important to make assumptions on the missing data between "missing at random" and/or "not missing at random". The assumption will be based on the report of the reasons for missing data and the distribution between allocated groups. If the data are assumed to be missing at random, we will only analyze the available data (i.e. ignoring the missing data). If the data are assumed not to be missing at random, we will input the missing data with replacement values, and treat these as if they were observed (e.g. last observation carried forward, imputing an assumed outcome such as assuming all were poor outcomes, imputing the mean, and imputing based on predicted values from a regression analysis). We will perform sensitivity analysis of the primary outcome on these assumptions to detect the impact of assumption modifications on the results.

Assessment of heterogeneity

We will examine heterogeneity of treatment effects between trials qualitatively with the Chi2 test with a significance level at P < 0.1. We will use the I2 statistic of inconsistency to quantify possible heterogeneity (Deeks 2011). We will use the following rough guide to interpret heterogeneity.

  • 0% to 40%: might not be important;

  • 30% to 60%: may represent moderate heterogeneity;

  • 50% to 90%: may represent substantial heterogeneity; and

  • 75% to 100%: considerable heterogeneity.

We will explore potential sources of heterogeneity through subgroup stratification by age, treatment used before the maintenance randomisation (i.e. whether allogeneic or auto transplant or chemotherapy alone have been used), allocation concealment, blinding and size of studies. We will use the tests for interaction to test for differences between subgroup results.

Assessment of reporting biases

If at least 10 studies are included, we will inspect the funnel plot of the treatment effect against the precision of trials (plots of the log of the RR for efficacy against the SE) and estimate potential asymmetry that may indicate selection bias (the selective publication of trials with positive findings) or methodological flaws in the small studies. We will statistically test by means of a linear regression test. We will consider P < 0.1 as significant for this test. If there are less than 10 studies, we will not adopt funnel plots because the power of the test is too low to distinguish chance from real asymmetry (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 enter the data into Review Manager (RevMan 2011). A second review author will check it for accuracy. For dichotomous data, we will estimate RRs and their CIs using the Mantel‐Haenszel method for the primary meta‐analysis, and repeat the statistical analysis, adopting a random‐effects model using the DerSimonian Laird method in terms of sensitivity analysis (Higgins 2011c). For time‐to‐event data, we will pool the log HR for time‐to‐event outcomes using an inverse variance method. If the HR and its SE or CI are not reported, we will estimate 'O‐E' and 'V' statistics indirectly using the methods described by Parmar 1998 and Tierney 2007. HRs or RRs less than 1.0 are in favour of maintenance treatment.

Subgroup analysis and investigation of heterogeneity

We will assess the heterogeneity of treatment effects by a Chi² test with a significance level at P < 0.1 and we will quantify it with the I² statistic (Deeks 2001). We will explore potential sources of heterogeneity through stratifying the patient subgroups according to:

  • age (younger adults age < 60 years; older adults age ≥ 60 years);

  • paediatric patients (age < 15 years) versus adult patients (age ≥ 15 years);

  • different types of definitions of AML (i.e. > 20% blasts versus >= 30% blasts);

  • treatment used before the maintenance randomisation (allogeneic stem cell transplants versus autologous stem cell transplants versus chemotherapy alone);

  • Patients receiving interleukin‐2 therapy before the maintenance randomisation versus those not receiving interleukin‐2;

  • different types of intervention (whether patients in the intervention group received other maintenance chemotherapy or not); and

  • doses of IL‐2 (as reported in the primary literature).

Sensitivity analysis

We will perform sensitivity analyses based on:

  • quality components, including full‐text publications versus abstracts, preliminary results versus mature results, and published versus unpublished data;

  • random‐effects model; and

  • risk of bias (by omitting studies judged to be of high risk of bias).