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. 2021 Jan 7;56(6):1341–1351. doi: 10.1038/s41409-020-01187-5

Overt gastrointestinal bleeding following haploidentical haematopoietic stem cell transplantation: incidence, outcomes and predictive models

Xueyan Sun 1,2,3,4,#, Yan Su 1,2,3,4,#, Xiao Liu 1,2,3,4,#, Yuanyuan Zhang 1,2,3,4, Yun He 1,2,3,4, Wei Han 1,2,3,4, Qi Chen 1,2,3,4, Huan Chen 1,2,3,4, Yu Wang 1,2,3,4, Yifei Cheng 1,2,3,4, Fengqi Liu 1,2,3,4, Fengrong Wang 1,2,3,4, Yao Chen 1,2,3,4, Gaochao Zhang 1,2,3,4, Xiaodong Mo 1,2,3,4, Haixia Fu 1,2,3,4, Yuhong Chen 1,2,3,4, Jingzhi Wang 1,2,3,4, Xiaolu Zhu 1,2,3,4, Lanping Xu 1,2,3,4, Kaiyan Liu 1,2,3,4, Xiaojun Huang 1,2,3,4, Xiaohui Zhang 1,2,3,4,✉
PMCID: PMC8189916  PMID: 33414512

Abstract

Gastrointestinal bleeding (GIB) accounts for a significant proportion of life-threatening bleeding cases occurring after allogeneic haematopoietic stem cell transplantation (allo-HSCT). However, data on GIB after haploidentical HSCT (haplo-HSCT) are not available. A total of 3180 patients received haplo-HSCT at Peking University People’s Hospital from January 2015 to November 2019, and GIB occurred in 188 of these patients (incidence of 5.9%). Platelet counts <30 × 109/L, viral hepatitis, acute kidney injury (AKI), gastrointestinal disease or bleeding before HSCT and sinusoidal obstruction syndrome (SOS) were determined to be significant risk factors for the occurrence of GIB after haplo-HSCT. Grade III-IV acute graft-versus-host disease (aGVHD), AKI, thrombotic microangiopathy (TMA), disseminated intravascular coagulation (DIC) and gastrointestinal disease or bleeding before HSCT were significantly related to mortality in patients with GIB after haplo-HSCT. The predictive models developed for the occurrence and mortality of GIB performed well in terms of discrimination, and they might assist clinicians with personalised strategies for GIB prevention and treatment in patients after haplo-HSCT.

Subject terms: Signs and symptoms, Risk factors

Introduction

Allogeneic haematopoietic stem cell transplantation (allo-HSCT) has been demonstrated to be the most effective therapy for various malignant as well as nonmalignant haematological diseases. However, the chance of patients receiving human leucocyte antigen (HLA)-matched donors is low because of the deficiency of sibling and unrelated donors in China [1–3]. In recent decades, our centre has successfully developed an approach for haplo-HSCT with a myeloablative regimen and granulocyte colony-stimulating factor-primed bone marrow and/or peripheral blood grafts. Numerous studies have suggested a comparable curative effect of haplo-HSCT performed using this approach for various haematological diseases [4–8]. Therefore, haplo-HSCT, with universal donor availability and a similar efficiency to HLA-matched HSCT, has gradually become a mainstream method for allo-HSCT [1, 3].

The wide use of haplo-HSCT has inevitably led to a variety of complications after transplantation [9–12], with bleeding complications due to various reasons being one of the most significant. Conditioning regimens, including antithymocyte immunoglobulin, and some posttransplant complications, such as GVHD and infection, can result in haemostatic and coagulation disturbances [13–16], thus increasing the risk of bleeding after transplantation. Numerous studies have shown that bleeding after transplantation is associated with reduced survival in patients [17–21]. The gastrointestinal tract is one of the most common bleeding sites after HSCT, and bleeding at this site is often more severe than that in other bodily locations except for pulmonary haemorrhage [18, 20]. However, most previous studies focused on overall bleeding after HSCT rather than only the gastrointestinal tract, and the analyses of these studies might not fully represent the features of GIB [17–20, 22–25]. Two other studies did focus on GIB after HSCT; however, one study targeted patients with primary systemic amyloidosis [22], and the other focused on only severe GIB [23]; both studies were relatively incomplete.

Thus, we herein focused on this topic, describing the incidence, clinical features, outcomes, risks and prognostic factors of GIB in patients receiving haplo-HSCT. Furthermore, to the best of our knowledge, predictive models for GIB after HSCT have not been developed, and we therefore developed predictive models for the occurrence and mortality of GIB after haplo-HSCT, which could have important implications for individualised prevention and therapeutic strategies for GIB following haplo-HSCT.

Methods

Patients

This was a retrospective, nested, case-control study carried out from January 2015 to November 2019. A total of 4312 consecutive patients received HSCT at Peking University People’s Hospital, among which 3180 received haplo-HSCT. Based on medical records, 214 patients were diagnosed with GIB. Patients without documented overt GIB (haematemesis, melena, or haematochezia) and those who developed overt GIB before HSCT were excluded. Finally, 188 patients with overt GIB after haplo-HSCT were included in the case group (Fig. 1). For each case, three patients without GIB among 3180 patients with haplo-HSCT were randomly selected comprise the control group in accordance with the following matching criteria: time of haplo-HSCT (±3 months) and length of follow-up (±6 months). All the patients in our study signed informed consent forms based on the Declaration of Helsinki, and this study was approved by the Institutional Review Board of Peking University.

Fig. 1. Flow chart of patient screening.

Fig. 1

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HSCT haematopoietic stem cell transplantation, allo allogenic, auto autogenic, HLA human leucocyte antigen, FOBT faecal occult blood test, GIB gastrointestinal bleeding.

Conditioning regimens and prophylaxis of GVHD

For patients with haplo-HSCT in our study, the conditioning regimens included cytarabine, busulfan, cyclophosphamide, semustine and antithymocyte immunoglobulin. Cytarabine was given at a dosage of 4 g/m2/d on days −10 and −9, and busulfan was given at a dosage of 3.2 mg/kg/d from days −8 to −6. Cyclophosphamide was administered at a dosage of 1.8 g/m2/d on days −5 and −4, and semustine was administered at a dosage of 250 mg/m2/d on day −3. Antithymocyte immunoglobulin was used at a dosage of 2.5 mg/kg/d from days −5 to −2. The prophylactic regimens for GVHD, cyclosporine, mycophenolate mofetil and short-term methotrexate as previously described [26], were administered to all patients after haplo-HSCT. The diagnoses and grades of aGVHD and chronic GVHD (cGVHD) were based on established guidelines and criteria [27].

Definitions

Overt GIB was defined as haematemesis, melena or haematochezia [28–30]. GIB was recognised as severe (sGIB) if it met one of the following criteria: (1) overt GIB with signs of haemorrhagic shock [23, 31], (2) overt GIB resulting in a decrease in haemoglobin of ≥2 g/dL [32, 33] or at least a 20% decrease in haematocrit levels [34–39], and (3) overt GIB requiring at least two units of packed red blood cells [23, 31–39]. Patients without any of the features described above constituted the non-severe GIB group [40].

Evaluation of GIB

Endoscopic examination was performed for patients with GIB after they agreed to participate in the study. The anatomical site and cause of GIB were identified by reviewing the endoscopic, histological and microbiological data, and the attribution of bleeding causes was based on a previous report [23]. GVHD was recognised as the single bleeding cause when typical appearance and histology were observed and cultures and immunohistochemistry analyses of viruses and fungi were negative. When evidence of GVHD and infection was found, both were regarded as the causes of bleeding. Other bleeding causes, such as gastritis and solitary ulcers, were based on the clinical and endoscopic findings.

Development of predictive models

To determine the risk and prognostic factors for GIB after haplo-HSCT, potential variables were evaluated using univariate Cox analysis, and the variables with a P value < 0.1 were then selected for backward stepwise multivariate Cox proportional hazards regression analysis. According to the previous prediction methods [41–44], predictive models for the occurrence of GIB and mortality in patients with GIB were developed based on the independent risk and prognostic factors in backward stepwise multivariate Cox analysis. The weighted point value proportional to the β regression coefficient values in multivariate regression analysis was assigned for each factor. The area under the receiver operating characteristic curve (AuROC) was used to assess the performances of the predictive models.

Statistical analysis

Continuous variables in our study are shown as medians (ranges) and were compared with Mann–Whitney U tests. Pearson’s Chi-square test and Fisher’s exact test were applied to compare categorical variables. Outcomes described by the cumulative incidence of overall survival (OS), non-relapse mortality (NRM) and relapse were evaluated by the Kaplan–Meier method and the log-rank test. OS was defined as the time of death for any reason after transplantation. NRM was defined as deceased without recurrence of primary disease following HSCT. Relapse was defined as over 5% blasts in bone marrow or the occurrence of blasts in peripheral blood or intramedullary infiltration of blasts. P values < 0.05 (two-sided) were considered statistically significant.

Results

Baseline patient characteristics

GIB occurred in 188 patients following haplo-HSCT (incidence of 5.9%). The baseline characteristics of the two groups are shown in Table 1. Patients with GIB were older than those without (median age 29 vs. 25 years, P = 0.002). A higher proportion of male patients was observed in patients with GIB, however, there were similar distribution of gender between patients with GIB and the controls. Gastrointestinal disease or bleeding before HSCT and viral hepatitis were more frequently observed in patients with GIB, and more patients with GIB experienced grade III-IV aGVHD, intestinal infection and TMA than patients in the control group. Platelet counts before the onset of bleeding in patients with GIB were lower than those in control patients (33 vs. 60 × 109/L, P = 0.000). There were no differences in underlying diseases, HLA mismatching, blood type compatibility, donor-recipient sex mismatching, engraftment time or history of alcohol intake between the two groups.

Table 1.

Baseline characteristics in patients with GIB and matched controls after haplo-HSCT.

Variables GIB (n = 188) Control (n = 564) P
Age at HSCT, years 29 (2–68) 25 (1–63) 0.002
Gender (n, %) 0.297
  Male 111 (59.0) 358 (63.5)
  Female 77 (41.0) 206 (36.5)
Time of GIB (post-HSCT) (days) 46 (1–892) /
Underlying disease, n (%) 0.111
  AML 68 (36.1) 193 (34.2)
  ALL 62 (33.0) 214 (37.9)
  CML 5 (2.7) 13 (2.3)
  AA 15 (7.9) 73 (12.9)
  MDS 24 (12.8) 47 (8.3)
  Lymphoma 6 (3.2) 8 (1.4)
  Others 8 (4.3) 16 (3.0)
ABO mismatch, n (%) 95 (50.5) 256 (45.4) 0.221
Donor-recipient sex mismatch, n (%) 87 (46.3) 233 (41.3) 0.233
HLA, n (%) 0.475
  3/6 164 (87.2) 471 (83.5)
  4/6 21 (11.2) 81 (14.4)
  5/6 3 (1.6) 12 (2.1)
MNC (×108/kg, mean ± SD) 8.61 ± 1.73 8.74 ± 2.36 0.791
CD34+ (×106/kg, mean ± SD) 2.41 ± 1.32 3.07 ± 4.85 0.002
Engraftment time, d (range)
  Neutrophil 13 (8–25) 13 (9–28) 0.491
  Platelet 18 (7–295) 16 (7–259) 0.114
aGVHD, n (%) 0.000
  0–II 84 (44.7) 528 (93.6)
  III–IV 104 (55.3) 36 (6.4)
Extensive cGVHD, n (%) 17 (9.0) 38 (6.7) 0.293
SOS 2 (1.1) 1 (0.2) 0.156
TMA 13 (6.9) 8 (1.4) 0.000
DIC 8 (4.3) 17 (3.0) 0.411
AKI 38 (20.2) 14 (2.5) 0.000
Intestinal infection 62 (33.0) 29 (5.1) 0.000
CMV viremia 112 (59.6) 355 (62.9) 0.410
Platelet count before GIB, 109/L 33 (3–324) 60 (4–356) 0.000
Diabetes mellitus 10 (5.3) 18 (3.2) 0.182
Hypertension 20 (10.6) 38 (6.7) 0.083
Viral hepatitis 22 (11.7) 18 (3.2) 0.000
Gastrointestinal disease or bleeding before HSCT 19 (10.1) 8 (1.4) 0.000
Alcohol, n (%) 6 (3.2) 8 (1.4) 0.127
Median follow-up time after HSCT, d (range) 380 (34–1808) 418 (3–1797) 0.273
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GIB gastrointestinal bleeding, AML acute myeloblastic leukaemia, ALL acute lymphoblastic leukaemia, CML chronic myeloid leukaemia, AA aplastic anaemia, MDS myelodysplastic syndrome, HLA human leucocyte antigen, aGVHD acute graft-versus-host disease, cGVHD chronic graft-versus-host disease, SOS sinusoidal obstruction syndrome, TMA thrombotic microangiopathy, DIC disseminated intravascular coagulation, AKI acute kidney injury, CMV cytomegalovirus, HSCT haematopoietic stem cell transplantation.

GIB after haplo-HSCT

The median time for the first GIB event was 46 days (range, 1–892 days) after haplo-HSCT. GIB presented as melena (17 patients, 9.0%), haematemesis (37 patients, 19.7%) and haematochezia (130 patients, 69.1%), with four patients (2.1%) presenting with both haematemesis and melena. Endoscopic evaluation was conducted for four patients with melena or haematemesis and for 95 patients with haematochezia. Among patients receiving endoscopic evaluation, GIB was detected in the oesophagus (1/99), duodenum (2/99), stomach (1/99), small intestine (29/99), colon (33/99), rectum (3/99) and at multiple sites (28/99). No bleeding foci were detected in two patients. The causes of GIB were diverse, with the most common single cause of bleeding being GVHD (56/99), followed by solitary ulcers (6/99), infection (3/99) and gastritis (1/99). Multiple bleeding causes were found in 26 patients; GVHD and gut infection both contributed to the occurrence of GIB in 25 patients, and one patient bled due to GVHD and TMA. The causes of bleeding in seven patients were not determined.

Among patients with GIB, 102 patients (54.3%) experienced severe GIB. The clinical characteristics of patients with severe and non-severe GIB as well as the latest laboratory data before GIB onset were shown in Table S1. The two groups were similar in terms of age at HSCT, sex, time of GIB onset, history of alcohol intake and some comorbidities. Compared with those of patients with non-severe GIB, the platelet counts of patients with severe GIB were significantly lower, and the prothrombin time/international normalised ratio was significantly longer. Some biochemical indicators, including total bilirubin and glucose, were present at significantly higher concentrations in patients with severe GIB than in those with non-severe GIB, while the concentration of albumin was lower in patients with severe GIB.

Outcomes

The OS of patients with GIB was significantly reduced (P = 0.000, Fig. 2a), and the NRM was higher in these patients than in those without GIB (P = 0.000, Fig. 2c). The cumulative incidence of relapse was not different between patients with GIB and the control group (P = 0.765, Fig. 2b). Among patients with GIB, the OS of patients with severe GIB was significantly lower (P = 0.000, Fig. 2d) and the NRM (P = 0.000, Fig. 2f) and cumulative incidence of relapse (P = 0.000, Fig. 2e) were higher than in those without severe GIB. Notably, both severe GIB and non-severe GIB significantly decreased OS (Fig. 2g, j) and increased the NRM (Fig. 2i, l) in patients after haplo-HSCT.

Fig. 2. Clinical outcomes of patients with GIB after haplo-HSCT.

Fig. 2

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Overall survival (a), incidence of relapse (b) and non-relapse mortality (c) for patients with GIB and without GIB after haplo-HSCT. The comparison of overall survival (d), incidence of relapse (e) and non-relapse mortality (f) of patients with severe GIB and non-severe GIB. The impact of severe GIB on overall survival (g), incidence of relapse (h) and non-relapse mortality (i) after haplo-HSCT. The impact of non-severe GIB on overall survival (j), incidence of relapse (k) and non-relapse mortality (l) after haplo-HSCT.

Predictors for the occurrence of GIB

The univariate and multivariate analysis results are presented in Table 2. According to the univariate analysis results, age > 30 years, SOS, AKI, platelet counts <30 × 109/L, viral hepatitis and gastrointestinal disease or bleeding before HSCT were significantly related to the occurrence of GIB after haplo-HSCT. In the multivariate analysis, the independent risk factors for GIB included platelet counts <30 × 109/L, viral hepatitis, AKI, gastrointestinal disease or bleeding before HSCT and SOS.

Table 2.

Risk factors for GIB after haplo-HSCT.

Variables Univariate P value Multivariate
HR 95% P value
Age > 30 0.004 1.069 0.786–1.454 0.670
Male 0.212
ABO mismatch 0.147
Donor-recipient sex mismatch 0.199
SOS 0.038 6.105 1.471–25.341 0.013
DIC 0.097 1.301 0.633–2.675 0.474
AKI 0.000 3.115 2.110–4.599 0.000
CMV viremia 0.148
Platelet counts < 30 × 109/L 0.000 2.408 1.785–3.248 0.000
Viral hepatitis 0.000 1.965 1.244–3.102 0.004
Gastrointestinal disease or bleeding before HSCT 0.000 3.780 2.334–6.122 0.000
Diabetes mellitus 0.153
Alcohol 0.092 1.384 0.605–3.168 0.441
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GIB gastrointestinal bleeding, SOS sinusoidal obstruction syndrome, DIC disseminated intravascular coagulation, AKI acute kidney injury, CMV cytomegalovirus, HSCT haematopoietic stem cell transplantation.

Predictive model for GIB

According to the above findings, a predictive model for GIB was developed based on the independent risk factors and β-coefficients that were obtained by multivariable Cox regression analysis (Table 3). Thus, the total score of each patient, ranging from 0 to 9 points, was determined. On the basis of each their scores, we categorised the 752 patients into three groups for GIB prediction: low risk (0–1 point), intermediate risk (2–3 points) and high risk (4–9 points). There were 667 patients in the low-risk group, 73 patients in the intermediate-risk group and 12 patients in the high-risk group; the corresponding GIB rates of each group were 19.5%, 63.0% and 100%, respectively (Table S2). The estimations of GIB occurrence following haplo-HSCT in each group are presented in Fig. 3. The mortality rate of patients after haplo-HSCT was 12.9% in the low-risk group, 43.8% in the intermediate-risk group and 83.3% in the high-risk group (Fig. 4, P = 0.000). The performance of our predictive model was good in terms of discrimination (AuROC = 0.705, 95% CI, 0.659–0.752, P = 0.000, Fig. 5). Furthermore, the nomogram plot for the predictive model was presented as Fig. S1.

Table 3.

Predictive model for GIB after haplo-HSCT.

Variables HR (95% CI) P value Multivariate regression coefficient Points
Platelet count < 30 × 109/L 2.433 (1.811–3.268) 0.000 0.889 1
Viral hepatitis 1.966 (1.248–3.098) 0.004 0.676 1
AKI 3.256 (2.237–4.739) 0.000 1.180 2
Gastrointestinal disease or bleeding before HSCT 3.770 (2.327–6.107) 0.000 1.327 2
SOS 6.323 (1.542–25.922) 0.010 1.844 3
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GIB gastrointestinal bleeding, AKI acute kidney injury, HSCT haematopoietic stem cell transplantation, SOS sinusoidal obstruction syndrome.

Fig. 3. Estimation of GIB occurrence stratified by the predictive model.

Fig. 3

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Probability of gastrointestinal bleeding (GIB) after haploidentical haematopoietic stem cell transplantation (haplo-HSCT) among patients of low-risk, intermediate-risk and high-risk group stratified by the predictive model.

Fig. 4. Survival of patients stratified by the predictive model for GIB.

Fig. 4

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Overall survival after haploidentical haematopoietic stem cell transplantation (haplo-HSCT) of patients of low-risk, intermediate-risk and high-risk groups stratified by the predictive model for gastrointestinal bleeding (GIB).

Fig. 5. Performance of the predictive model on discriminating GIB following haplo-HSCT.

Fig. 5

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The area under the receiver operating characteristic curve (AuROC) of the predictive model for GIB following haploidentical haematopoietic stem cell transplantation (haplo-HSCT).

Prognostic factors

Among patients with GIB, 66 patients (35.1%) experienced death during the study. To further identify the prognostic factors for patients with GIB, age, sex, transplant complications prior to GIB, laboratory data on the occurrence of GIB and comorbidities were analysed. In multivariate analysis, grade III–IV aGVHD, AKI, TMA, DIC and gastrointestinal disease or bleeding before HSCT were significantly related to mortality in patients with GIB after haplo-HSCT (Table 4).

Table 4.

Prognostic factors of patients with GIB after haplo-HSCT.

Variables Patients (n, %) Univariate P value Multivariate
Death (−) Death(+) HR 95% P value
Age > 30 54 (44.3) 37 (56.1) 0.045 1.427 0.833–2.444 0.195
Male 68 (55.7) 43 (65.2) 0.296
Transplant complications prior to GIB
 III–IV aGVHD 60 (49.2) 44 (66.7) 0.004 2.302 1.340–3.952 0.003
 Extensive cGVHD 11 (9.0) 6 (9.1) 0.566
 TMA 2 (1.6) 11 (16.7) 0.000 5.539 2.745–11.179 0.000
 SOS 0.120
 DIC 1 (0.8) 7 (10.6) 0.000 4.535 1.963–10.478 0.000
 AKI 16 (13.1) 22 (33.3) 0.000 2.621 1.510–4.548 0.001
 Intestinal infection 41 (33.6) 21 (31.8) 0.934
 CMV viremia 67 (54.9) 45 (68.2) 0.087 1.306 0.749–2.277 0.346
 Gastrointestinal disease or bleeding before HSCT 7 (5.7) 12 (18.2) 0.002 3.748 1.925–7.296 0.000
Laboratory data at the occurrence of GIB
 Hb < 80 g/L 59 (48.4) 38 (57.6) 0.056 1.319 0.785–2.215 0.296
 Platelet count < 30 × 109/L 58 (47.5) 34 (51.5) 0.421
 Platelet count < 20 × 109/L 33 (27.0) 26 (39.4) 0.083 1.390 0.802–2.410 0.241
Comorbidities
 Viral hepatitis 14 (11.5) 8 (12.1) 0.659
 Hypertension 9 (7.4) 11 (16.7) 0.109
 Diabetes mellitus 5 (4.1) 5 (7.6) 0.422
 Alcohol 4 (3.3) 2 (3.0) 0.997
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GIB gastrointestinal bleeding, aGVHD acute graft-versus-host disease, cGVHD chronic graft-versus-host disease, SOS sinusoidal obstruction syndrome, TMA thrombotic microangiopathy, DIC disseminated intravascular coagulation, AKI acute kidney injury, CMV cytomegalovirus, HSCT hematopoietic stem cell transplantation.

Predictive model for mortality

Based on the prognostic factors we identified and their β-coefficients obtained by multivariable Cox regression analysis, we established a predictive model for mortality in patients with GIB after haplo-HSCT (Table 5), with scores ranging from 0 to 7 points. Estimation of death was therefore divided into three groups: low risk (0–1 points), intermediate risk (2–3 points) and high risk (4–7 points); the mortality rates of each group were 25.3%, 60.6% and 100%, respectively (Fig. 6). The performance of our predictive model for mortality was good in terms of discrimination (AuROC = 0.728, 95% CI, 0.651–0.805, P = 0.000, Fig. 7). Furthermore, the nomogram plot for the predictive model was presented as Fig. S2.

Table 5.

Predictive model for mortality of patients with GIB after haplo-HSCT.

Variables HR (95% CI) P value Multivariate regression coefficient Points
III–IV aGVHD 2.347 (1.390–3.965) 0.001 0.853 1
AKI 2.957 (1.748–5.001) 0.000 1.084 1
Gastrointestinal disease or bleeding before HSCT 3.438 (1.805–6.550) 0.000 1.235 1
TMA 6.040 (3.075–11.864) 0.000 1.798 2
DIC 4.736 (2.102–10.670) 0.000 1.555 2
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GIB gastrointestinal bleeding, aGVHD acute graft-versus-host disease, TMA thrombotic microangiopathy, DIC disseminated intravascular coagulation, AKI acute kidney injury, HSCT haematopoietic stem cell transplantation.

Fig. 6. Estimation of mortality of patients with GIB stratified by the predictive model.

Fig. 6

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Probability of mortality of patients with gastrointestinal bleeding (GIB) after haploidentical haematopoietic stem cell transplantation (haplo-HSCT) stratified by the predictive model.

Fig. 7. Performance of the predictive model on discriminating mortality of patients with GIB following haplo-HSCT.

Fig. 7

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The area under the receiver operating characteristic curve (AuROC) of the predictive model for mortality of patients with gastrointestinal bleeding (GIB) following haploidentical haematopoietic stem cell transplantation (haplo-HSCT).

Discussion

GIB accounts for a significant proportion of bleeding events, especially in cases of life-threatening bleeding after allo-HSCT [18]. As haplo-HSCT is becoming the main method of transplantation [1, 3], systemic investigations of GIB following haplo-HSCT are needed.

In our study, the incidence of GIB after haplo-HSCT was 5.9%, which is lower than that in previous reports [17, 22, 24, 29]. This result might be due to the discrepancy of the underlying disease, transplantation type and therapeutic strategy for patients. The gastrointestinal tract is frequently involved in a variety of posttransplant complications, with GVHD being one of the most common after allo-HSCT, and gastrointestinal tract involvement is seen in 74% of patients with aGVHD [45] and 30% of patients with cGVHD [46]. More than half of all patients with severe gastrointestinal GVHD are reported to experience GIB [47], and other complications, such as conditioning toxicity, infection and TMA, often affect the gut [48, 49]. Thus, the causes resulting in the occurrence of GIB after HSCT vary, and the time of GIB onset is not always fixed. The time span of GIB onset was relatively large in our study, and the causes and anatomical sites of bleeding were diverse as determined by reviews of the endoscopic, histological and microbiological data of patients with GIB who underwent endoscopic examination. GVHD was demonstrated to be the most common single cause in our study, which is consistent with a previous report [23].

Bleeding, especially GIB, has been reported to correlate with a poor prognosis following HSCT [21, 50]. Similarly, we found that GIB had a profound negative influence on the OS and NRM of patients receiving haplo-HSCT. While previous studies suggested that the severity of bleeding affects patient survival [21], our results indicated that both severe and non-severe GIB after haplo-HSCT could decrease the OS and increase the NRM of patients.

In recent years, many studies have revealed risk factors for bleeding complications after HSCT, with numerous complications after HSCT, such as low platelet counts, grade III–IV aGVHD, extensive cGVHD, TMA and SOS, being related to increased risks of posttransplant bleeding[18–20]. As GIB is one of the most common manifestations of GVHD and TMA [47, 51, 52], we did not include these factors in our risk analysis. Low platelet counts and SOS were indeed identified as factors leading to GIB following haplo-HSCT in our study. Other independent risk factors for GIB identified herein included viral hepatitis, AKI and gastrointestinal disease or bleeding before HSCT. An increased risk of GIB in patients with viral hepatitis has been reported [53]. Patients positive for hepatitis viral antigens are at high risk of viral reactivation because of the long period of immunosuppression after HSCT [54, 55]. Thus, viral hepatitis was included in the risk factor analysis and it was revealed as an independent risk factor for GIB following haplo-HSCT. Impairment of renal function has been shown to increase the risk of GIB in solid organ transplantation [56, 57]. Many drugs used after HSCT are nephrotoxic, and some posttransplant complications also affect renal function; thus, AKI might become a risk factor for GIB after haplo-HSCT. Indeed, we found that AKI was related to the occurrence of GIB in patients receiving haplo-HSCT, and a history of gastrointestinal disease or bleeding has been shown to be associated with GIB in patients with other clinical backgrounds [44, 58–60]. In accordance with previous findings, gastrointestinal diseases, such as peptic ulcers and bleeding before transplantation were revealed to be independent risk factors for GIB after haplo-HSCT. Alcohol has always been known to have a substantial effect on the occurrence of GIB [61–65]. However, alcohol was not correlated with GIB after haplo-HSCT in our research, potentially because most patients entirely avoided alcohol before HSCT [66]. Until now, no study has investigated the relationship between alcohol and GIB after haplo-HSCT. As this was a retrospective single-centre study and detailed information about alcohol intake of patients was not readily available, additional large-scale multicentre studies are needed to clarify whether alcohol influences GIB after haplo-HSCT.

As GIB has a negative influence on the prognosis of patients after haplo-HSCT, it is essential to estimate the risk of its occurrence. According to the risk prediction methods used in a nested case-control study [41, 42], we developed a predictive model for GIB after haplo-HSCT. The GIB and survival rates of each risk group categorised by this model were significantly different, and the AuROC was relatively high, which indicated that the model was good for predicting the risk of GIB after haplo-HSCT when used for the derived samples; however, further external validation is needed.

In total, 66 patients (35.1%) with GIB died in our study, although bleeding was not always the direct cause of death. Once patients experience GIB, it is of great significance to identify the risk factors for mortality, and we therefore we tried to analyse the prognostic factors for patients with GIB. Grade III–IV aGVHD, AKI, TMA, DIC and gastrointestinal disease or bleeding before HSCT were associated with mortality in patients with GIB. Then, the risk model for mortality in patients with GIB was developed, and it performed well.

Some limitations also exist in our study. First, this was a single-centre retrospective study, and the results might not be completely appropriate for analyses of GIB after haplo-HSCT. Furthermore, selection bias is inevitable in nested cohort studies. In addition, multicentre prospective studies are required to validate our predictive models for GIB and mortality in patients with GIB after haplo-HSCT.

In summary, our study demonstrated that GIB is a severe complication following haplo-HSCT that negatively influences the prognosis of patients. Independent risk and prognostic factors were identified for GIB in our study to develop predictive models for the occurrence and mortality of GIB after haplo-HSCT, which might assist clinicians with personalised GIB prevention and therapeutic strategies.

Supplementary information

Table S1 (40KB, doc)
Table S2 (14.1KB, docx)
Figure S1 (130.4KB, pdf)
Figure S2 (129KB, pdf)

Acknowledgements

This work was supported by the National Key Research and Development Programme of China (No. 2017YFA0105503, No. 2017YFA0105500), Key Programme of National Natural Science Foundation of China (No. 81730004), National Natural Science Foundation of China (No. 81670116), Foundation for Innovative Research Groups of the National Natural Science Foundation of China (81621001), Beijing Natural Science Foundation (No. 7171013, H2018206423) and Beijing Municipal Science and Technology Commission (No. Z171100001017084).

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Footnotes

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

These authors contributed equally: Xueyan Sun, Yan Su, Xiao Liu

Supplementary information

The online version of this article (10.1038/s41409-020-01187-5) contains supplementary material, which is available to authorised users.

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Supplementary Materials

Table S1 (40KB, doc)
Table S2 (14.1KB, docx)
Figure S1 (130.4KB, pdf)
Figure S2 (129KB, pdf)

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