Abstract
This systematic review and meta-analysis aimed to determine whether hematogones in patients with hematopoietic disorders after allogeneic hematopoietic stem cell transplantation (allo-HSCT) are associated with clinical outcomes.
We searched the MEDLINE, Embase, Cochrane Central Register of Controlled Trials, ClinicalTrials.gov, and World Health Organization International Clinical Trials Registry Platform databases from their inception to March 2023. The primary outcome in the summary of findings was three-year relapse-free survival (RFS), and secondary outcomes in the summary of findings included three-year relapse, non-relapse mortality (NRM), overall survival (OS), acute and chronic graft-versus-host disease (GVHD), and infection. The certainty of evidence was determined using the grading of recommendation assessment, development, and evaluation approaches. A systematic review and meta-analysis of outcome measures were conducted using a random-effects model. This study protocol was registered in the Open Science Framework.
A total of six studies (including 888 patients) were included in the meta-analysis. Hematogones were related to favorable three-year RFS (risk ratio (RR) = 1.84; 95% confidence interval (CI) = 1.01 to 3.34) and favorable NRM (RR = 0.14; 95% CI = 0.04 to 0.51), OS (RR = 1.51; 95% CI = 1.13 to 2.02), and acute GVHD (RR = 0.44; 95% CI = 0.33 to 0.59). The certainty of the evidence was low for RFS, NRM, OS, and acute GVHD. Evidence regarding the association between hematogones, relapse, and infections is uncertain. Hematogones may be a prognostic factor for long-term prognosis and acute adverse events in patients with hematopoietic disorders after allo-HSCT. Further studies are required to address the long-term life-threatening events.
Keywords: grade approach, systematic review, prognostic value, meta-analysis, hematogones
Introduction and background
Allogeneic hematopoietic stem cell transplantation (allo-HSCT) is an important and potentially curative treatment for many malignant and non-malignant hematopoietic bone marrow disorders, such as aplastic anemia [1]. However, the complications associated with allo-HSCT are critical. For example, acute and chronic graft-versus-host disease (GVHD) manifests as the most prevalent and critical complication [2,3]. Infections pose a substantial risk of fatality during immune reconstruction [4], which may span up to two years [5]. Moreover, the incidence of relapse is as high as 30-40% [6] and remains a significant cause of mortality after allo-HSCT [7]. Accurate prediction and management of these outcomes are essential for successful allo-HSCT [8].
Hematogones, which denote benign B-lymphocyte precursors, appear during bone marrow function recovery after induction therapy, consolidation therapy, or allo-HSCT [9,10]. Hematogones correlate with better overall survival (OS) and relapse-free survival (RFS), and a lower incidence of treatment-related mortality and GVHD in patients after allo-HSCT [11]. Additionally, their presence is a predictor of a lower incidence of infections [12,13]. However, to our knowledge, no systematic review has summarized the evidence across these outcomes or presented the clinical applicability of hematogones.
To investigate the prognostic value of hematogones in the clinical course of allo-HSCT, this systematic review and meta-analysis estimated an average effect across studies and assessed each study’s limitations as well as gaps in the entire published literature. This study also provided information to guide a further study in the context of study design.
Review
Methodology
Compliance with Reporting Guidelines
Using a pre-specified protocol (Open Science Frame Registry ID: CRD42018105511), we conducted a systematic review of the relevant literature in agreement with the recommendations of the Cochrane Handbook [14] and the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines [15]. We confirmed that this systematic review was PRISMA-compliant by consulting the PRISMA 2020 checklist [16].
Eligibility Criteria
The target population comprised patients with hematological disorders who underwent allo-HSCT. Hematogones in bone marrow aspiration or biopsy smear are defined as lymphoid precursor cells with diameters varying from 10 to 20 µm, scant cytoplasm, and densely homogeneous nuclear chromatin [9]. The bone marrow tests used to evaluate hematogones include bone marrow aspiration and biopsy. Flow cytometry (FCM) is defined as low-side scatter, intermediate expression of CD45, and bright expression of at least both CD10 and CD19 or terminal deoxynucleotidyl transferase [9]. We adopted the results of positive and negative hematogones reported in each study because there is no clear cutoff value for the percentage of hematogones present in the total bone marrow cells. The number of cells in the bone marrow aspiration smear or events in the FCM analysis was not subjected to inquiry. We set the period for evaluating hematogones to be approximately the time of engraftment, with an allowable range from day 10 to day 100.
The primary outcome was the three-year RFS. The secondary outcomes were the proportion of one-, three-, and five-year relapses; non-relapse mortality (NRM); overall survival (OS); incidence of grade Ⅱ-IV acute GVHD at one year; moderate-to-severe chronic GVHD at three years; total infections at one year; bacterial, viral, and fungal infections at one year; and serum immunoglobulin (Ig)G levels at three months.
We included prospective and retrospective cohort studies that assessed the clinical predictive value of hematogones. No restrictions were applied based on the language of publication, country, observation period, or year of publication. Published articles were included, whereas conference abstracts were excluded.
We excluded patients presenting with the following results from the bone marrow samples: (1) recurrence, (2) residual disease, or (3) incomplete chimerism. The definitions of these were adopted from the respective studies. No exclusion was made based on donor source or disease status at the time of allo-HSCT.
Search Strategy and Selection of Studies
World Health Organization International Clinical Trials Registry Platform and ClinicalTrial.gov. via search portals. The search was performed on March 15, 2023, using a set of suitable search terms, including “allo-HSCT,” “hematogones,” “B-lymphoid precursor cells,” and related terms (Table 1). We also attempted to identify other relevant studies by manually searching the reference lists of included studies. If the candidate study did not contain the necessary information, the authors were contacted to obtain the relevant information. Two reviewers (Hirotaka Mori and Yuki Sato) independently screened the titles and abstracts of each study obtained by the search to determine whether they met the inclusion criteria. The reviewers conducted a full-text review to assess the eligibility of each candidate study. Disagreements were resolved through discussion with a third reviewer (Daisuke Koyama).
Table 1. Search strategy.
| Database | Search strategies |
| CENTRAL via Cochrane Library | #1. MeSH descriptor: [Stem Cell Transplantation] explode all trees |
| #2. (transplant*):ti,ab,kw | |
| #3. #1 OR #2 | |
| #4. (Hematogone*):ti,ab,kw | |
| #5. (Haematogone*):ti,ab,kw | |
| #6. #4 OR #5 | |
| #7. MeSH descriptor: [Precursor Cells, B-Lymphoid] explode all trees | |
| #8. (“b cell precursor*”):ti,ab,kw | |
| #9. (“b lymphoid precursor*”):ti,ab,kw | |
| #10. (“b lymphocyte precursor*”):ti,ab,kw | |
| #11. #7 OR #8 OR #9 OR #10 | |
| #12. #6 OR #11 | |
| #13. #3 AND #12 | |
| MEDLINE via PubMed | #1. “Stem Cell Transplantation”[MeSH Terms] |
| #2. transplant*[Title/Abstract] | |
| #3. #1 OR #2 | |
| #4. Hematogone*[Title/Abstract] | |
| #5. Haematogone*[Title/Abstract] | |
| #6. #4 OR #5 | |
| #7. “Precursor Cells, B-Lymphoid”[MeSH Terms] | |
| #8. “b cell precursor*”[Title/Abstract] | |
| #9. “b lymphoid precursor*”[Title/Abstract] | |
| #10. “b lymphocyte precursor*”[Title/Abstract] | |
| #11. #7 OR #8 OR #9 OR #10 | |
| #12. #6 OR #11 | |
| #13. #3 AND #12 | |
| EMBASE via Dialog | S1. EMB.EXACT.EXPLODE(“stem cell transplantation”) |
| S2. TI(transplant*) OR AB(transplant*) | |
| S3. S1 OR S2 | |
| S4. TI(Hematogone*) OR AB(Hematogone*) | |
| S5. TI(Haematogone*) OR AB(Haematogone*) | |
| S6. S4 OR S5 | |
| S7. EMB.EXACT.EXPLODE(“pre B lymphocyte”) | |
| S8. TI(“b cell precursor*”) OR AB(“b cell precursor*”) | |
| S9. TI(“b lymphoid precursor*”) OR AB(“b lymphoid precursor*”) | |
| S10. TI(“b lymphocyte precursor*”) OR AB(“b lymphocyte precursor*”) | |
| S11. S7 OR S8 OR S9 OR S10 | |
| S12. S6 OR S11 | |
| S13. S3 AND S12 | |
| S14. (S3 AND S12) not (rtype.exact(“Conference Abstract” OR “Conference Paper” OR “Conference Review” OR “Editorial” OR “Chapter”)) | |
| WHO ICTRP | in the Title: (b cell precursor* OR hematogone*) AND (stem cell transplantation) |
| ClinicalTrials.gov | Condition or disease: (“b cell precursors” OR “b cell precursor” OR “hematogones” OR “hematogone”) AND (stem cell transplantation) |
Data Extraction and Quality Assessment
Two reviewers (Hirotaka Mori and Yuki Sato) independently extracted study-level data using pre-specified forms. Disagreements regarding data extraction were resolved through discussion. Where necessary, we contacted the authors of the studies for which sufficient information was not available. The risk of bias of each study was assessed independently by two reviewers (Hirotaka Mori and Daisuke Koyama) using the Quality in Prognostic Studies (QUIPS) tool [17]. We assessed the confounding domains using the QUIPS tool. Differences in opinion regarding the assessment of risk of bias were resolved through discussion between the two reviewers.
Data Analysis
For three-year RFS; three-year, one-year, and five-year relapses; NRM; OS; incidence of acute grade II-IV GVHD at one year; moderate-to-severe chronic GVHD at three years; total infections at one year; and bacterial, viral, and fungal infections as dichotomous variables and pooled risk ratios (RR) with 95% confidence interval (CI) were provided. The mean differences with 95% CI were calculated for serum IgG levels as continuous variables.
To calculate the number of events, we multiplied the percentage of events at a prespecified time point using the Kaplan-Meier method [18] or Gray’s method [19] using the effective sample size [20]. The calculations consisted of three steps. First, we reconstructed the order of events and censored the outcomes from published or ordered Kaplan-Meier curves or cumulative incidence curves using DigitizeIt software (version 2.5.9) (http://www.digitizeit.de/) and applied established algorithms [21,22]. Second, we estimated the standard errors of event probabilities from the reconstructed data. Finally, we used the effective sample size obtained from the Greenwood formula to calculate the RR and 95% CI [20]. The effective sample size is a measure of sample size that accounts for the precision obtained from observed right-censored data. Therefore, the effective sample size is smaller than the reported baseline sample size according to the number of censored patients in the original study.
We created a table of summary of findings including the overall grading of evidence certainty for each of the main outcomes, evaluated using the Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) approach [23].
All analyses were conducted using the Stata software version 17 (Stata Corp., College Station, TX, USA).
Results
Study Selection
Figure 1 shows the results of the literature search using the PRISMA 2020 flow diagram [16]. After removing duplicates, we screened 845 records, from which we reviewed 18 full-text documents, excluded 12 studies (Appendices), and, finally, included six articles [11-13,24-26]. Subsequently, we searched the references of the included studies. However, no articles among these fulfilled the inclusion criteria.
Figure 1. The Preferred Reporting Items for Systematic Reviews and Meta-Analysis 2020 flow diagram.
From Page et al. [15].
Study Characteristics
Table 2 presents the characteristics of the included studies. The six studies included a total of 888 patients. Two studies defined hematogones based on smear findings [11,25], whereas four defined them based on FMC [12,13,24,26]. The cutoff point of the hematogones varied from 0% to 5%. The percentage of positive hematogones ranged from 26.1% to 75.8%. Table 3 shows the details of the patient characteristics, including disease categories and status, donor sources, preconditioning regimen, GVHD prophylaxis, the follow-up period of survivors, and the test day of hematogones. Figure 2 shows the synthesized results. The extracted outcomes, determined a priori, differed across studies. The one- and three-year OS and acute GVHD outcomes were the most reported outcomes in this meta-analysis of four studies.
Table 2. Characteristics of the included studies.
Data were presented as numbers (percentages).
ND = not described; FCM = flow cytometry; BMT = bone marrow transplantation; CBT = cord blood transplantation
| Honebrink et al. [11] | Christopeit et al. [24] | Shima et al. [12] | Doki et al. [13] | Ishii et al. [25] | Ishio et al. [26] | |
| Publish year | 2012 | 2013 | 2013 | 2015 | 2017 | 2018 |
| Study types | Prospective | Retrospective | ND | ND | Retrospective | Retrospective |
| Sample size | Test day 21/100: 86/66 | 59 | 108 | 192 | 134 | 309 |
| Hematogones | ||||||
| Definition test | Smear | FCM | FCM | FCM | Smear | FCM |
| Cutoff percentage | Test day 21/100: 0/0.9 | 0.25 | 5 | 0.25 | 1.0 | 0.1 |
| Positive/Negative | Test day 21: 60/26 (69.8/30.2) Test day 100: 50/16 (75.8/24.2) | 24/35 (40.7/59.3) | 43/65 (39.8/60.2) | 78/114 (40.6/59.4) | 35/99 (26.1/73.9) | 117/192 (37.9/62.1) |
| Test days | 21 (n = 86) 100 (n = 66) | 100 | 30 | |||
| Median | 25/32 (BMT/CBT) | 41 | 30 | |||
| Minimum | 15/14 (BMT/CBT) | 20 | 17 | |||
| Maximum | 32/39 (BMT/CBT) | 77 | 71 | |||
| Note | The number of outcomes on test day 21 was not described | 16 patients who relapsed or died within 90 days were excluded | ||||
Table 3. Patient characteristics.
†: AML or MDS; ‡: Tac-based GVHD prophylaxis
BMT = bone marrow transplantation; CBT = cord blood transplantation; AML = acute myeloblastic leukemia; MDS = myelodysplastic syndrome; ALL = acute lymphoblastic leukemia; CML = chronic myeloblastic leukemia; ML = malignant lymphoma; CR = complete remission; ND = not described; NA = not applicable; PBSCT = peripheral blood stem cell transplantation; MAC = myeloablative conditioning; RIC = reduced-intensity conditioning; Tac = tacrolimus; sMTX = short-term methotrexate; MMF = mycophenolate mofetil; PTCY = post-transplant cyclophosphamide; FCM = flow cytometry
| Honebrink et al. [11] | Christopeit et al. [24] | Shima et al. [12] | Doki et al. [13] | Ishii et al. [25] | Ishio et al. [26] | |
| Diseases categories | ||||||
| AML | 88/66 (Test day 21/100) | 63 | 60† | 89 | 70 | 124 |
| MDS | 13 | 33 | 16 | 41 | ||
| ALL | 18 | 45 | 33 | 71 | ||
| CML | 7 | 6 | 13 | |||
| ML | 30 | 10 | 7 | 60 | ||
| Others | 8 | 2 | ||||
| Disease status | ||||||
| CR | 86/66 (test day 21/100) | 36 | 41 | 109 | 215 | |
| Non-CR/NA | 2/0 | 40 | 67 | 76 | 94 | |
| Donor sources | ||||||
| BMT | 1 | 49 | 192 | 172 | ||
| PBSCT | 74 | NA | 88 | |||
| CBT | 88 | 1 | 49 | 134 | 48 | |
| Preconditioning regimens | ||||||
| MAC | 88 | 25 | 66 | 154 | 127* | 158 |
| RIC | 51 | 42 | 38 | 7* | 151 | |
| GVHD prophylaxis | ND | |||||
| Tac and sMTX | 57 | 136 | 192 | |||
| CsA and sMTX | 13 | 36 | 56 | 128 | 77 | |
| Tac and MMF | 11 | |||||
| CsA and MMF | 59 | 15 | 6 | 2 | ||
| PTCY | 27 | |||||
| Others/unknown | 4 | |||||
| Follow-up period for survivors | ND | ND | ND | |||
| Median (days) | 605 | 78 months | 923 | |||
| Minimum range | 31 | 3 moths | 71 | |||
| Maximum range | 3252 | 153 months | 4188 | |||
Figure 2. Outcomes of the meta-analysis.
*: Subgroup analyses were performed.
†: Bone marrow biopsy on day 21 and other outcomes of the Honebrink et al. study on day 100.
‡: Unavailable information which our inquiry could not complement.
§: Data available upon request to the author.
The black circles indicate the outcomes of the study conducted by the authors.
RFS = relapse-free survival; NRM = non-relapse mortality; OS = overall survival; GVHD = graft-versus-host disease
Risk of Bias in the Included Studies
The QUIPS tool was used to assess the risk of bias of the included studies [17]. Figure 3 shows the risk of bias in the summary of the outcome findings. The risk of bias was assessed in five studies with a summary of the outcomes [11-13,25,26]. All five studies demonstrated a low risk of bias for study participation; however, all had a high risk of bias for study attrition and a moderate risk of bias for prognostic factor measurements. All five studies had a low risk of bias for outcome measurement of three-year RFS, relapse, NRM, and OS; however, a moderate risk of bias for outcome measurement was found in half of the four studies on acute GVHD [11,12] and all two studies on total infections [13,26]. There was no low risk of bias for study confounders, statistical analysis, or reporting.
Figure 3. Risk of bias for the summary of outcome findings.
D1: study participation; D2: study attrition; D3: prognostic factor measurement; D4: outcome measurement; D5: study confounding; D6: statistical analysis and reporting.
The red, yellow, and green blocks indicate high, moderate, and low risk, respectively.
RFS = relapse-free survival; NRM = non-relapse mortality; OS = overall survival; GVHD = graft-versus-host disease
Certainty of Evidence
Table 4 shows the summary of findings. The primary outcome of three-year RFS was reported in two studies [12,26]. Hematogones were significantly related to three-year RFS (RR = 1.84; 95% CI = 1.01 to 3.34; I2 = 86.0%; n = 353) (Figure 4); the certainty of the evidence was low. Regarding secondary outcomes, three-year relapse was analyzed in two studies [25,26]; the pooled RR was 1.04 (95% CI = 0.74 to 1.46; I2 = 0%; n = 402) (Figure 5), and the certainty of the evidence was very low. Three-year NRM was analyzed in three studies [12,25,26]; the pooled RR was 0.14 (95% CI = 0.04 to 0.51; I2 = 19.7%; n = 514) (Figure 6), and the certainty of the evidence was low. Three-year OS was analyzed in four studies [11,12,25,26]; the pooled RR was 1.51 (95% CI = 1.13 to 2.02; I2 = 81.6%; n = 594) (Figure 7), and the certainty of the evidence was low. Acute GVHD was analyzed in four studies [11-13,26]; the pooled RR was 0.44 (95% CI = 0.33 to 0.59; I2 = 0%; n = 692) (Figure 8), and the certainty of the evidence was low. No study reported the outcome of chronic GVHD, as defined in the protocol. Infections were analyzed in two studies [13,26]; the pooled RR was 0.55 (95% CI = 0.42 to 0.73; I2 = 0%; n = 498) (Figure 9), and the certainty of the evidence was very low.
Table 4. Summary of findings from six studies focused on hematogones in patients after allo-HSCT.
*: The corresponding risk (and its 95% CI) is based on the assumed risk in the comparison group and the relative effect (and its 95% CI) estimated for the intervention group. Assumed risk was median of control risks.
GRADE Working Group grades of evidence: High certainty: We are very confident that the true effect lies close to that of the estimate of the effect. Moderate certainty: We are moderately confident in the effect estimate; the true effect is likely to be close to the estimate of the effect, but there is a possibility that it is substantially different. Low certainty: Our confidence in the effect estimate is limited; the true effect may be substantially different from the estimate of the effect. Very low certainty: We have very little confidence in the effect estimate; the true effect is likely to be substantially different from the estimate of effect
a: We did not consider the domain of study confounding and statistical analysis and reporting in the risk of bias for judging the certainty of the evidence.
b: Downgraded one point because of moderate or high risk of bias associated with attrition, prognostic factor measurement, and outcome measurement.
c: Downgraded one point as imprecise (few studies).
d: Downgraded two points as imprecise (confidence interval).
e: Downgraded two points because of moderate or high risk of bias associated with attrition, prognostic factor measurement, and outcome measurement.
allo-HSCT = allogeneic hematopoietic stem cell transplantation; CI = confidence interval; RR = risk ratio; NA = not applicable; RFS = relapse-free survival; NRM = non-relapse mortality; OS = overall survival; GVHD = graft versus host disease; NA = not applicable
| Outcome | Illustrative comparative risks* (95% CI) | Relative effect (95% CI) | Number of participants (studies) | Certainty of the evidence a (GRADE) | |
| Assumed risk | Corresponding risk | ||||
| Comparison | Exposure | ||||
| Three-year RFS | Study population | RR 1.84 (1.01 to 3.34) | 353 (2 studies) | ⊕⊕⊝⊝ Low b, c | |
| 463 per 1,000 | 852 per 1,000 (468 to 1,000) | ||||
| Three-year relapse | Study population | RR 1.04 (0.74 to 1.46) | 402 (2 studies) | ⊕⊝⊝⊝ Very low b, d | |
| 290 per 1,000 | 302 per 1,000 (215 to 423) | ||||
| Three-year NRM | Study population | RR 0.14 (0.04 to 0.51) | 514 (3 studies) | ⊕⊕⊝⊝ Low b, c | |
| 107 per 1,000 | 15 per 1,000 (4 to 55) | ||||
| Three-year OS | Study population | RR 1.51 (1.13 to 2.02) | 594 (4 studies) | ⊕⊕⊝⊝ Low b, c | |
| 537 per 1,000 | 811 per 1,000 (607 to 1,000) | ||||
| Acute GVHD | Study population | RR 0.44 (0.33 to 0.59) | 692 (4 studies) | ⊕⊕⊝⊝ Low b, c | |
| 398 per 1,000 | 175 per 1,000 (131 to 235) | ||||
| Chronic GVHD | Study population | NA | NA | NA | |
| NA | NA | ||||
| Infections | Study population | RR 0.55 (0.42 to 0.73) | 498 (2 studies) | ⊕⊝⊝⊝ Very low c, e | |
| 439 per 1,000 | 241 (184 to 321) | ||||
Figure 4. Forest plot of three-year RFS.
RFS = relapse-free survival; HG = hematogones; + = positive; - = negative
Figure 5. Forest plot of three-year relapse.
HG = hematogones; + = positive; - = negative
Figure 6. Forest plot of three-year NRM.
NRM = non-relapse mortality; HG = hematogones; + = positive; - = negative
Figure 7. Forest plot of three-year OS.
OS = overall survival; HG = hematogones; + = positive; - = negative
Figure 8. Forest plot of acute GVHD.
GVHD = graft-versus-host disease; HG = hematogones; + = positive; - = negative
Figure 9. Forest plot of total infections.
HG = hematogones; + = positive; - = negative
Subgroup Analysis
The prespecified subgroup analysis for the primary outcome of three-year RFS revealed a similar direction of effect to the overall group [26]. We observed no notable differences among the bone marrow (RR = 1.28; 95% CI = 1.00 to 1.65), peripheral blood stem cell (RR = 1.70; 95% CI = 1.14 to 2.52), and cord blood transplantation subgroups (RR = 1.38; 95% CI = 0.80 to 2.40). We also observed no notable differences among disease categories of acute myeloid leukemia or myelodysplastic syndromes (RR = 1.15; 95% CI = 0.77 to 1.74), acute lymphoblastic leukemia (RR = 1.41; 95% CI = 0.96 to 2.07), and lymphoma (RR = 1.43; 95% CI = 0.95 to 2.14).
Additional Outcomes
Data on one-year relapse were available from three studies [13,25,26]; the pooled RR was 0.91 (95% CI = 0.67 to 1.23; I2 = 0%; n = 616) (Figure 10). Data on five-year relapse were available from one study [25]; the RR was 1.32 (95% CI = 0.53 to 3.27; I2 = NA; n = 123) (Figure 11).
Figure 10. Forest plot of one-year relapse.
HG = hematogones; + = positive; - = negative
Figure 11. Forest plot of five-year relapse.
HG = hematogones; + = positive; - = negative
Data on one-year NRM were available from four studies [11,13,25,26]; the pooled RR was 0.19 (95% CI = 0.07 to 0.50; I2 = 20.2%; n = 679) (Figure 12). Data on five-year NRM were obtained from one study [25]; the RR was 0.30 (95% CI = 0.10 to 0.96; I2 = NA; n = 103) (Figure 13).
Figure 12. Forest plot of one-year NRM.
HG = hematogones; + = positive; - = negative; NRM = non-relapse mortality
Figure 13. Forest plot of five-year NRM.
HG = hematogones; + = positive; - = negative; NRM = non-relapse mortality
Data on one-year OS were available from four studies [13,24-26]; the pooled RR was 1.14 (95% CI = 0.97 to 1.32; I2 = 78.2%; n = 662) (Figure 14). Data on five-year OS were available from one study [25]; the RR was 1.16 (95% CI = 0.88 to 1.53; I2 = NA; n = 113) (Figure 15).
Figure 14. Forest plot of one-year OS.
HG = hematogones; + = positive; - = negative; OS = overall survival
Figure 15. Forest plot of five-year OS.
HG = hematogones; + = positive; - = negative; OS = overall survival
Data on bacterial infections at one year were available from two studies [13,26]; the pooled RR was 0.54 (95% CI = 0.33 to 0.89; I2 = 0%; n = 490) (Figure 16). Data on viral infections at one year were available from two studies [13,26]; the pooled RR was 0.49 (95% CI = 0.32 to 0.73; I2 = 0%; n = 486) (Figure 17). Data on fungal infections at one year were available from two studies [13,26]; the pooled RR was 0.15 (95% CI = 0.03 to 0.63; I2 = 0%; n = 497) (Figure 18). Data on IgG levels at three months were available in two studies [25,26]; the mean difference was 97.3 mg/dL (95% CI = 43.5 to 151.1; I2 = 0%; n = 443) (Figure 19).
Figure 16. Forest plot of bacterial infections.
HG = hematogones; + = positive; - = negative
Figure 17. Forest plot of viral infections.
HG = hematogones; + = positive; - = negative
Figure 18. Forest plot of fungal infections.
HG = hematogones; + = positive; - = negative
Figure 19. Forest plot of IgG levels.
IgG = immunoglobulin G; HG = hematogones; + = positive; - = negative
Differences Between the Protocol and the Review
As the largest number of integrated studies was four, we could not assess publication bias using funnel plots and Egger tests. Owing to the small sample size, we could not conduct planned sensitivity analyses for the primary outcomes. (i) exclusion of studies with a high risk in QUIPS domains, (ii) exclusion of the prognostic values of hematogones evaluated from 100 median days after allo-HSCT, and (iii) when the meta-analytic result of the primary outcome showed significant heterogeneity. We could not perform a meta-regression of the cutoff levels for positive or negative hematogones because of the small number of included studies. We also searched for case-control studies but found none that met the eligibility criteria.
Discussion
This systematic review included six studies evaluating the prognostic value of hematogones in 888 patients with hematopoietic disorders after allo-HSCT. The presence of hematogones was related to lower cumulative incidence estimates of three-year NRM, and, as a result, demonstrated an improvement in three-year RFS. Subgroup analysis by donor source and disease category consistently demonstrated a favorable three-year RFS. Acute GVHD and infections were the major causes of NRM in the allo-HSCT setting [27,28], and less acute GVHD and infections translated into lower NRM. Additionally, our results on RFS, NRM, acute GVHD, and infections suggest a favorable OS in patients with positive hematogones [29]. The benefits of less acute GVHD and fewer infections in patients with hematogones may outweigh the uncertain effects of relapse.
Our results imply that hematogones are a prognostic factor for survival and acute GVHD in patients with hematopoietic disorders after allo-HSCT. Currently, the useful prognostic factors for patients in complete remission after allo-HSCT are limited. A cohort study showed that the prognostic values of neutrophil and platelet engraftment times for the three-year OS rate were almost the same in patients with engraftment before day 28 and those with engraftment between days 28 and 42 [30]. A meta-analysis showed that engraftment syndrome (ES) was a negative prognostic factor, and the incidence of ES was associated with a higher incidence of acute and chronic GVHD, NRM, and decreased OS compared with the absence of ES [31]. Our meta-analysis confirmed that hematogones are a prognostic factor for favorable survival and acute adverse outcomes in patients in complete remission. These positive prognostic values indicate the potential therapeutic strategies. The prevalence of hematogones further supports the clinical decision of physicians to follow a consensus on the use of low-dose steroids for the management of grade 2 or lower acute GVHD with isolated cutaneous and upper gastrointestinal symptoms [32]. In cases of first-line systemic therapy for acute GVHD [33], slow tapering rates of steroid doses to avoid exacerbation or recurrence of acute GVHD might be one of the acceptable ways considering the low risk of primary disease recurrence and infection in patients with hematogones.
The evidence of hematogones is uncertain regarding long-term adverse events, such as relapse and infection, and there is no information about chronic GVHD. In particular, results regarding relapse, in which the confidence interval crosses the line of null effects, should be interpreted with caution, although this does not mean that hematogones have no prognostic value [34]. The significant effect sizes of bacterial, viral, and fungal infections and serum IgG levels did not reinforce confidence in the results regarding total infections. Severe chronic GVHD can be fatal following allo-HSCT [2]. However, no study has reported the grade of chronic GVHD according to the National Institutes of Health criteria [35]. Further studies are required to evaluate the grade of chronic GVHD based on these criteria.
This review has several strengths. The results of this review are based on the best available evidence after a comprehensive search. Additionally, we used a systematic methodology that followed a written a priori protocol developed according to the PRISMA statement [16]. We used the GRADE approach [23] to assess the certainty of evidence. This method strengthens the recommendations for the use of hematogones as a prognostic factor in the current clinical practice of allo-HSCT.
There are some potential limitations to the risk of bias and study methods. First, attrition bias was judged to be high in all studies. The included studies did not report the number of participants lost to follow-up or the reasons, which could have systematically biased the association between the prognostic factors and prognosis [36]. Additionally, the number of events was estimated using the Kaplan-Meier and Gray’s method [18,19] because no other information was available. This method tends to overestimate the number of events to the extent that patients are lost to follow-up or censored [37]. However, to address the issue of overestimated event proportions, we widened the 95% CI using an effective sample size to account for censoring [20]. Second, the data extracted for the meta-analysis were reported in crude form and were not adjusted for the various confounders listed in Table 3, such as disease status at allo-HSCT, human leukocyte antigen match, preconditioning regimen, and GVHD prophylaxis [13,25,26]. The adjusted effect size may have reduced the borderline significance of our meta-analysis [38]. Third, the variation in the cutoff levels of hematogones between studies may have influenced the results. We planned to perform a meta-regression to address this heterogeneity but were unable to do so because of the limited number of studies that included a subgroup analysis. Further research is needed to address the high attrition bias and loss to follow-up, unadjusted reports of confounding factors, and optimal cutoff levels of hematogones.
Conclusions
Hematologists may use hematogones as prognostic factors for long-term prognosis and acute unfavorable events in patients with hematopoietic disorders following allo-HSCT. There is still room for improvement in methods of primary research to lower the risk of bias. Further cohort studies are warranted to address the methodological issues and the uncertainty regarding long-term life-threatening events.
Acknowledgments
We thank Dr. Ishio and Dr. Konuma for additional analyses. We also thank secretary P.
Appendices
Table 5. Characteristics of excluded studies.
| Reason for exclusion | Study |
| Studies without cutoff values of hematogones | Storek et al. Am J Hematol. 1996; 52: 82-9 Storek et al. Blood. 2001; 98: 489-91. Sánchez-García et al. Haematologica. 2006; 91: 340-7. Kahng et al. Korean J Lab Med. 2007; 27: 406-13 Fedoriw et al. Biol Blood Marrow Transplant. 2012;18: 968-73. Mensen et al. Blood. 2014; 124: 963-72 Sarvaria et al. Blood. 2016; 128: 1346-61. Bohmann et al. Ann Hematol. 2017; 96: 299-310. Skert et al. PLoS One. 2017; 12: e0175337. Schultz KR, Blood. 2020; 135: 1287-98 |
| Impossible to contact | Hagino et al. Tokyo Jikeikai Med J. 2006; 121: 17-26 |
| Patients with acute lymphoblastic leukemia after consolidation therapy | Wang et al. Int J Lab Hematol. 2016; 38: 246-55 |
| Study including 32% of cases with a bone marrow examination at a time exceeding 100 days | Montesinos et al. Biol Blood Marrow Transplant. 2012; 18: 388-95 |
The authors have declared financial relationships, which are detailed in the next section.
Isao Yokota declare(s) a grant and personal fees from KAKENHI, AMED, and Health, Labour and Welfare Policy Research Grants, Nihon Medi-Physics, Chugai Pharmaceutical Co. and AstraZeneca . IY reports grants from KAKENHI, AMED, and Health, Labour and Welfare Policy Research Grants, research fund by Nihon Medi-Physics, and speaker fees from Chugai Pharmaceutical Co. and AstraZeneca outside the submitted work. The other authors declare that they have no competing financial interests. Takanori Teshima declare(s) a grant and personal fees from Merck Sharp and Dohme, Takeda, Kyowa-Kirin, Bristol-Myers Squibb, and Pfizer, Chugai, Kyowa-Kirin, Sanofi, Astellas, Teijin Pharma, Novartis, Fuji Pharma, Nippon Shinyaku, Takeda and Novartis, Janssen and Novartis. TT has received honoraria from Merck Sharp and Dohme, Takeda, Kyowa-Kirin, Bristol-Myers Squibb, and Pfizer; has received research funding from Chugai, Kyowa-Kirin, Sanofi, Astellas, Teijin Pharma, Novartis, Fuji Pharma, and Nippon Shinyaku; has served on an advisory board for Takeda and Novartis; and has participated in manuscript preparation as part of other financial interests for Janssen and Novartis.
Author Contributions
Concept and design: Hirotaka Mori, Daisuke Koyama, Yuki Kataoka, Shunsuke Taito, Isao Yokota
Acquisition, analysis, or interpretation of data: Hirotaka Mori, Daisuke Koyama, Yuki Sato, Yuki Kataoka, Shunsuke Taito, Takashi Ishio, Takanori Teshima, Isao Yokota
Drafting of the manuscript: Hirotaka Mori, Yuki Kataoka, Shunsuke Taito, Isao Yokota
Critical review of the manuscript for important intellectual content: Hirotaka Mori, Daisuke Koyama, Yuki Sato, Yuki Kataoka, Shunsuke Taito, Takashi Ishio, Takanori Teshima, Isao Yokota
Supervision: Hirotaka Mori, Yuki Kataoka, Shunsuke Taito, Isao Yokota
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