Meta-analysis: Effect of Prophylactic Hematopoietic Colony-Stimulating Factors on Mortality and Outcomes of Infection

Granulocyte colony-stimulating factor (G-CSF) and granulocyte-macrophage colony-stimulating factor (GM-CSF) are hematopoietic colony-stimulating factors (CSFs) that decrease the duration and severity of neutropenia in adults and children receiving chemotherapy for cancer and those undergoing stem-cell transplantation (SCT) (1, 2). Several systematic reviews have examined whether CSFs affect other outcomes of patients with cancer in different prophylactic settings (39). These reviews, which summarized data from 6 to 34 studies, usually found that CSFs reduced febrile neutropenia and documented infections. None found statistically significant reductions in infection-related mortality and all-cause mortality, although CIs around such estimates were wide given the rarity of these outcomes. Although no single trial or previous systematic review had sufficient power to exclude a clinically significant benefit of prophylactic CSFs on short-term all-cause mortality, we hypothesized that combining all available data from randomized trials in patients with cancer and in the SCT setting would improve the ability to determine whether CSFs influence this outcome. Thus, we sought to determine whether prophylactic CSFs decrease all-cause and infection-related mortality, as well as infections and febrile neutropenia, more than do placebo or no therapy in patients with cancer and patients undergoing SCT. We also performed stratified analyses and meta-regression to explore whether effects differed among certain subgroups of patients. Methods Data Sources and Searches We developed a protocol for the review and followed standard Quality of Reporting of Meta-Analyses (QUOROM) guidelines (10). We performed electronic searches of Ovid MEDLINE from 1966 to 24 April 2007, of EMBASE from 1980 to 26 April 2007, and of the Cochrane Central Register of Controlled Trials until the second quarter of 2006. The search strategy included the following Medical Subject Heading terms and text words: granulocyte colony-stimulating factor, granulocyte-macrophage colony-stimulating factor, neoplasms, stem cell transplant, and bone marrow transplant. We also used abbreviated, generic, and trade names for all available G-CSFs and GM-CSFs, including pegfilgrastim. The search was limited to randomized, controlled trials. We also contacted the pharmaceutical manufacturers of G-CSFs and GM-CSFs. Study Selection We defined inclusion and exclusion criteria a priori. Studies were included if 1) patients were randomly assigned to CSFs or to placebo or no therapy, 2) CSFs were given concurrently with or after initiation of chemotherapy or conditioning for SCT but before neutropenia developed, and 3) chemotherapy or conditioning regimens or other supportive care was not planned to systematically differ between study groups. We described reasons for excluding studies by using a hierarchical system that ranked reasons for exclusion in the following order: 1) absence of placebo or no-treatment group; 2) allocation not randomly assigned; 3) intervention not administered concurrently with or after initiation of chemotherapy, or SCT conditioning (we excluded studies of priming in which CSF therapy was initiated before chemotherapy) or administration not prophylactic; 4) systematically different chemotherapy or conditioning regimens; 5) systematically different supportive care; and 6) duplicate publication. Studies included in the meta-analysis were not restricted by language or publication status. Two reviewers independently evaluated the titles and abstracts of publications identified by the search strategy, and any publication thought to be potentially relevant by either reviewer was retrieved in full. The reviewers were not blinded to study authors or outcomes. Final inclusion of studies in the meta-analysis was determined by agreement of both reviewers. Agreement between reviewers was evaluated by using a statistic. Strength of agreement as evaluated by the statistic was defined as slight (= 0.00 to 0.20), fair (= 0.21 to 0.40), moderate (= 0.41 to 0.60), substantial (= 0.61 to 0.80), or almost perfect (= 0.81 to 1.00) (11). Data Extraction and Quality Assessment The primary outcome measure was short-term all-cause mortality. Wherever possible, we assessed this outcome at 1 month after the initiation of use of the study drug. If data at 1 month were not available, we used the closest data between 3 and 6 weeks for chemotherapy recipients and up to 100 days or survival to discharge for patients undergoing SCT. Secondary outcomes were infection-related mortality, documented infections, microbiologically documented infections, and febrile neutropenia. Other outcomes of interest were those related to other infections (sterile-site bacterial infections, documented fungal infections, and clinically documented infections), febrile neutropenia (durations of febrile neutropenia, fever, and neutropenia), and resource utilization (antibacterial and antifungal administration and duration of hospitalization). In principle, documented infections were composed of microbiologically and clinically documented infections; however, if detailed descriptions were not provided, we relied on the authors' categorization of infectious outcomes. Two reviewers extracted data. We attempted to contact all authors to obtain information not available in the retrieved reports; 29 responded, and 4 provided additional data. We assessed study quality by using elements of the Jadad scale (12), which examines adequacy of randomization, double-blinding, and description of withdrawals and dropouts. The primary purpose of the Jadad scale is to examine elements that may affect bias. We performed stratified analyses by elements that we felt to be the greatest threats to validity, namely double-blinding and concealed allocation (inability to determine which treatment the next participant will receive in the trial). However, for the purpose of describing the included studies, we also present the summary Jadad scale, which ranges from 0 to 5 and in which a higher score is associated with higher quality. We used the statistic to assess agreement in study quality as extracted by the two reviewers. Data Synthesis and Analysis This meta-analysis combined data at the study level and not at the individual-patient level. For all-cause and infection-related mortality, data were synthesized by using relative risk as the effect measure; a relative risk less than 1 suggests that CSFs are associated with a reduction in that outcome. For all-cause mortality, we also present the absolute risk reduction associated with CSF prophylaxis. Because several of the trials applied the assigned intervention after a single randomization to multiple cycles of chemotherapy and the results were presented in aggregate form, a different analytic approach was used for the nonsurvival categorical outcomes. When categorical data from multiple cycles or therapeutic groups (for example, different doses of CSFs) were available, events were aggregated and assumed to follow a Poisson distribution and are presented per cycle for the overall analyses. The outcome was expressed as the natural logarithm of the rate ratio, with the variance of the rate ratio determined by using the delta method (13). For continuous outcomes, we made the following assumptions to facilitate data synthesis: The mean can be approximated by the median; the range contains 6 SDs, the 95% CI contains 4 SEs, and the interquartile range contains 1.35 SDs. Continuous outcome variables were expressed as the mean difference, which represents the overall difference between CSF and placebo or no-therapy strategies. For example, the mean difference for fever duration is the overall difference in days of fever between CSF and placebo or no therapy, with negative numbers indicating that duration was shorter with CSFs. Effect sizes were weighted by their inverse variance. Because we anticipated heterogeneity between studies, we used a random-effects model (14) for all analyses. We explored the potential sources of heterogeneity with stratified analyses and random-effects meta-regression for the primary and secondary outcomes. We present stratified analyses by age group (pediatric, adult, or older patients), diagnosis (leukemia, solid tumor/lymphoma, or SCT), whether the primary study mandated the use of antibacterial prophylaxis (yes or no), CSF type (G-CSF or GM-CSF), timing of CSF administration (concurrent with chemotherapy or following completion of the chemotherapy cycle), concealed allocation (yes or no), and double-blinded design (yes or no). To examine the association of study-level characteristics and treatment effect, we fitted random-effects meta-regression models to the natural logarithm of the relative risks or rate ratios by using the PROC MIXED procedure in SAS statistical software, version 9.1 (SAS Institute, Cary, North Carolina). The natural logarithm of the relative risk or rate ratio was assumed to have a normal distribution, and a maximum likelihood method was used to estimate model variables. The random-effects meta-regression model included fixed effects for the covariates, and a random intercept term was specified to model residual heterogeneity not accounted for by the covariates. For the stratified analyses and meta-regressions, only studies that reported on a single stratum were included, to avoid double-counting. For example, studies that included both pediatric and adult patients but did not report data separately by age group were excluded from the stratified analysis and meta-regression for age. We explored the possibility of publication bias by examining funnel plots (15). The meta-analysis was performed by using Review Manager, version 4.2 (The Cochrane Collaboration, Oxford, United Kingdom). Meta-regression was performed by using SAS software. All tests of significance were 2-sided, and statistical significance was defined as a P value less than 0.05.