Financial impact of post-transplant complications among children undergoing allogeneic hematopoietic cell transplantation

Introduction Allogeneic Hematopoietic Cell Transplantation (allo HCT) is currently the only curative therapy for high-risk hematologic malignancies due to the immune response of the donor cells against the malignant cells (graft versus tumor effect; GVT), but with the cost of Graft Versus Host Disease (GVHD). Despite extensive research, very few predictors of GVHD and GVT have been identified to date. Additionally, clinical GVHD diagnosis can be challenging due to chemotherapy-related or infection-related organ toxicity manifestations, which further complicate prediction and treatment stratification algorithms. In order to study the mechanisms of GVHD and GVT and to identify potential GVHD markers we apply a novel approach, called Transcriptome Fingerprint Assay (TFA), relying on high frequency sampling and blood transcript profiling. The TFA is a multiplex microfluidics q-PCR based assay linked with a computational model for modular functional transcriptome analyses, uniquely tailored to answer complex questions on immune perturbations through frequent profiling of gene expression signatures from < 1 ml of blood (Chaussabel and Baldwin. Nat Rev Immunol 2014, Speake et al. Clin Exp Immunol 2017). This approach has been successfully applied to stratify patients' prognosis in autoimmune and infectious diseases (Banchereau R et al. Cell 2016, Dunning et al. Nat Immunol 2018). In our study we use the TFA to capture longitudinal immune signatures as dynamic "snapshots" of the patient's immune system after HCT. Hypotheses Fluctuations over-time in gene expression of allo HCT patients' immune system reflect the pathologic/disease control programs (GVHD/GVT) and may be used to identify diagnostic and predictive biomarkers. GVHD/GVT control immune programs depend on the "inner" interface between the donor immune-system and the recipient, and are influenced by external variables, as infections or drugs. These variables can affect the immune system-related gene expression and can be measured. Objectives To systematically measure gene expression signatures in immune perturbations post-allo HCT, in order to: Identify GVHD-related immune signatures consistent with clinical diagnosis of GVHD.Predict and stratify therapy-resistant GVHD and severe chronic GVHD, according to immune signatures.Identify links (causative and consequential) between GVHD, GVT, relapse, and other post-transplant immune perturbations (e.g. infections). Methods Enroll 250 allo HCT patients to populate a "GVHD cohort" and a "non-GVHD cohort" of 50 patients each, and 50 donors (healthy controls cohort) . Patients donate micro-quantities of blood (50 to 600 microliters), weekly until day 100 post-transplant and every 2 weeks thereafter until 2 years after transplant. Detailed clinical, laboratory and therapy annotations are captured during the follow-up. Gene expression of 264 immune-related genes for each sample are measured through Fluidigm BioMark high throughput qPCR system, and normalized to the geometric mean Ct of 8 housekeeping genes. Data interpretation is performed through TFA modular analyses and correlated with the clinical annotations. Results Results of three series of patients' samples are shown to exemplify the potential of TFA as a method to study the mechanisms of GVHD and GVT. All three patients underwent myeloablative peripheral blood stem cell transplant from an HLA identical sibling donor. Two patients developed steroid responsive-acute GVHD (patient #1: GVHD stage I was diagnosed on day 38 post HCT, patient #4: GVHD stage III was diagnosed on day 21 post HCT). One patient (Patient #6) did not develop clinical GVHD, but routine skin biopsy on day 80 revealed apoptotic cells consistent with subclinical skin GVHD. Principal Component Analysis (PCA) of the three patients' series is shown in Figure 1, the dynamic transcriptomes according to TFA modules of patients #1 and #6 are shown in Figure 2, and representative TFA modular fingerprints are shown in Figure 3. Conclusion We anticipate that using the TFA approach will help to fill knowledge gaps instrumental to solve clinical dilemmas related to allo HCT complications, and to improve the clinical outcomes of allo HCT patients. Disclosures No relevant conflicts of interest to declare.

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Predictors and Impact Of 30-Day Readmissions On Patient Outcomes and Healthcare Costs After Allogeneic Hematopoietic Cell Transplantation

Blood ◽

10.1182/blood.v122.21.1718.1718 ◽

2013 ◽

Vol 122 (21) ◽

pp. 1718-1718

Author(s):

Abraham Sebastian Kanate ◽

Sherri Rauenzahn ◽

Sonia Leadmon ◽

Quoc V. Truong ◽

Aaron Cumpston ◽

...

Keyword(s):

Health Care ◽

Hospital Discharge ◽

Cell Transplantation ◽

Hematopoietic Cell Transplantation ◽

Hematopoietic Cell ◽

Allogeneic Hematopoietic Cell Transplantation ◽

Index Admission ◽

Hospital Charges ◽

Post Transplant ◽

Cell Dose

Abstract Readmission within 30 days of hospital discharge has recently become an important topic of discussion and a measure of quality of care. Factors influencing 30-day readmissions and its impact on patient related outcomes are diverse. Allogeneic hematopoietic cell transplantation (allo-HCT) presents a unique medical setting that may be associated with higher readmission rates. We analyzed factors affecting 30-day readmissions, its impact on patient related outcomes and health care costs in allo-HCT patients. The study group included 91 consecutive patients with hematological malignancies who underwent related (n=44) or unrelated donor (n=47), peripheral blood allo-HCT after conditioning with fludarabine and busulfan +/- thymoglobulin. Subjects were divided into 2 groups; readmission (R-gp), n=35 if they were readmitted within 30 days of hospital discharge after the index hospitalization for a planned allo-HCT, or to no readmission (NR-gp), n=56. The baseline characteristics did not differ between the 2 groups (Table 1). Overall 38% (n=35) required readmission with a median time to readmission of 14 days (range, 1-29). Causes for readmission included documented infections (n=12), cardio-pulmonary complications (n=10), fever (n=6), gastrointestinal disorders (n=4), and graft-versus-host disease (n=3). Median length of stay was 3 days (range, 1-34). In multivariate analysis only documented infection during the index admission predicted 30-day readmission, OR 5.24; 95% CI 1.42-19.32; p=0.01. Caregiver type (spouse vs. others); and number of caregivers (1 vs. >1) did not influence readmission. With a median follow up of 1 year for surviving patients, the estimated overall survival (OS) was 58% and 67% in the R-gp and NR-gp respectively, OR 1.07, 95% CI 0.55-2.06, p=0.85. The 1-yr non-relapse mortality (NRM) in R-gp and NR-gp was 74% and 84% respectively, OR 1.13, 95% CI 0.42-3.03, p=0.80. The median post-transplant hospital charges (inpatient + outpatient) in the R-gp and NR-gp were 85,115.45 USD (mean 93,925.26, range 32,014.86-242,519.35) and 45,083.09 USD (mean 69,142.6, range 10,714.78-485,456.08), p=0.0002. In conclusion, except for infections during the index admission, no other baseline demographic, social, disease or treatment related factors influenced 30-day readmissions after allo-HCT. 30-day readmission status did not adversely affect OS or NRM, but it significantly increased the 100-day hospital charges. Acknowledging the limitation of our study included its retrospective nature and small sample size, we conclude that 30-day readmission status does not portend poor post transplant outcomes. However, it is associated with higher health care costs.Table 1Baseline Patient CharacteristicsReadmission (n=35)Not Readmitted (n=56)P-ValueMedian age (range)56 (17-72)54 (22-68)0.23Male (%)21 (60)34 (61)0.99Malignancy type, n (%)0.93ALL/AML/MDS23 (65.7)39 (70)CLL/CML2 (5.7)3 (5)Hodgkin/NHL/Others10 (28.6)14 (25)Disease risk, n (%)0.18Low16 (45.7)24 (43)Intermediate3 (8.6)13 (23)High16 (45.7)19 (34)Disease status, n (%)0.49Chemosensitive23 (66)41 (73)Resistant12 (34)15 (27)Prior number of therapy, median (range)2 (1-6)2 (0-6)0.65Prior radiation therapy, n (%)2 (6)8 (14)0.31Prior autologous transplantation, n (%)2 (6)6 (11)0.71KPS, median (range)80 (60-100)85 (70-100)0.44HCT-CI, median (range)2 (0-7)1 (0-5)0.31Patients receiving ATG, n (%)23 (66)31 (55)0.38Donor type, n (%)Unrelated19 (54)28 (50)0.83Related16 (46)28 (50)HLA mismatch, n (%) §0.99Allele level1 (2)3 (5)Antigen level1 (2)1 (2)Infused CD34 cell dose, median (range) ¶6.5 (2.7-12.8)6.5 (1.8-15.1)0.98Infused CD3 cell dose, median (range) Ŧ31.3 (9.6-58.5)32.4 (11.5-94.5)0.48GVHD prophylaxis, n (%)0.83MTX + calcineurine inhibitor22 (63)33 (59)MMF + calcineurine inhibitor13 (37)23 (41)*High resolution HLA typing at the allele level for A, B, C and DRB-1 for all patients.¶Cell dose x 106/kg patient body weightŦCell dose x 107/kg patient body weight Disclosures: No relevant conflicts of interest to declare.

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