Individualized prediction of leukemia‐free survival after autologous stem cell transplantation in acute myeloid leukemia

Limited Contribution of Donor Characteristics to One-Year Survival After Hematopoietic Stem Cell Transplantation

A large number of association studies have related donor characteristics to survival after bone marrow transplantation, for leukemia in general and specifically for acute myeloid leukemia (AML) patients. However, population-based differences often do not hold at the single transplant level. We test whether transplantation outcomes can be predicted at the single-patient level and whether such predictions can be used to better choose donors. The analysis was performed on a mixture of different diseases or with AML only, and with either patient and donor information or donor information only. We analyzed 3671 8-of-8 HLA-matched AML donor-recipient pairs and tested whether the outcome, including 1-year total and event-free survival, can be predicted from patient and donor-related factors. We used multiple machine learning and survival analysis methods. The best method is a fully connected neural network. Multiple outcomes can be predicted, with area under the specificity-sensitivity curve (AUC) values between 0.54 and 0.67 for the different outcomes. The patient age has a strong impact on prediction. However, for a given patient, when only donor or transplant information is used, limited prediction accuracy of 0.54 to 0.56 AUC for event-free survival and survival is obtained. Graft-versus-host disease and rejection after 1 year have slightly higher AUC values of around 0.59, whereas the relapse prediction accuracy was random. All donors' characteristics have a limited influence on the quality of hematopoietic stem cell transplantation for fully matched donors. Many factors with a population effect on survival have a very limited effect when combined with all other factors in a single-donor predictive model.

Autologous stem cell transplantation (ASCT) for acute myeloid leukemia in patients in first complete remission after one versus two induction courses: A study from the ALWP of the EBMT

BACKGROUND

Achieving complete remission (CR) is the main goal in AML treatment and a prerequisite for successful autologous stem cell transplantation (ACT).

METHODS

Comparing results of peripheral blood ACT in patients with AML in CR1 attained following 1 versus 2 chemotherapy courses transplanted in 2000-2019.

RESULTS

Patients 1532 (84%) with one and 293 (16%) patients with two induction chemotherapies courses (a total of 1825 patients) were included in the study. Follow-up was 7.9 (95% CI: 7.4-8.4) and 7.7 (95% CI: 7.0-8.6) years (p = 0.8). Time from diagnosis to ACT was 4.7 (range, 3.9-5.8) versus 5.7 (range, 4.7-7.1) months (p < 0.001), respectively. Leukemia free survival (LFS) and overall survival (OS) at 5 years were inferior for patients achieving CR1 with 2 versus 1 course of chemotherapy: 26.6% versus 41.7% (HR = 1.42 [95% CI: 1.22-1.66], p < 0.001) and 36.2% versus 53.3%, (HR = 1.48 [95% CI: 1.25-1.75], p < 0.001), and 5-year relapse incidence (RI) was higher: 67.2% versus 52.3%, (HR = 1.46 [95% CI: 1.25-1.72], p < 0.001). Five-year non-relapse mortality (NRM) was 6.2% versus 6.0% for patients with 2 versus 1 chemotherapy courses, and did not differ significantly (HR = 1.31 [95% CI: 0.81-2.10], p = 0.27).

CONCLUSIONS

LFS and OS were inferior and relapse rate was higher in AML patients who received two inductions chemotherapy courses to reach CR1 before being autografted. AML patients who required 2 induction courses to achieve remission, may be offered allogeneic transplantation rather than an autologous one in an attempt to reduce their high RI and improve outcomes.

A Review of Artificial Intelligence Applications in Hematology Management: Current Practices and Future Prospects

Background

Machine learning (ML) and deep learning (DL) methods have recently garnered a great deal of attention in the field of cancer research by making a noticeable contribution to the growth of predictive medicine and modern oncological practices. Considerable focus has been particularly directed toward hematologic malignancies because of the complexity in detecting early symptoms. Many patients with blood cancer do not get properly diagnosed until their cancer has reached an advanced stage with limited treatment prospects. Hence, the state-of-the-art revolves around the latest artificial intelligence (AI) applications in hematology management.

Objective

This comprehensive review provides an in-depth analysis of the current AI practices in the field of hematology. Our objective is to explore the ML and DL applications in blood cancer research, with a special focus on the type of hematologic malignancies and the patient’s cancer stage to determine future research directions in blood cancer.

Methods

We searched a set of recognized databases (Scopus, Springer, and Web of Science) using a selected number of keywords. We included studies written in English and published between 2015 and 2021. For each study, we identified the ML and DL techniques used and highlighted the performance of each model.

Results

Using the aforementioned inclusion criteria, the search resulted in 567 papers, of which 144 were selected for review.

Conclusions

The current literature suggests that the application of AI in the field of hematology has generated impressive results in the screening, diagnosis, and treatment stages. Nevertheless, optimizing the patient’s pathway to treatment requires a prior prediction of the malignancy based on the patient’s symptoms or blood records, which is an area that has still not been properly investigated.

The Clinical Value of Procalcitonin in the Neutropenic Period After Allogeneic Hematopoietic Stem Cell Transplantation

The diagnostic value of procalcitonin and the prognostic role of PCT clearance remain unclear in neutropenic period after allogeneic hematopoietic stem cell transplantation introduction. This study evaluated 219 febrile neutropenic patients (116, retrospectively; 103, prospectively) who underwent allo-HSCT from April 2014 to March 2016. The area under the receiver operator characteristic curve (AUC) of PCT for detecting documented infection (DI) was 0.637, and that of bloodstream infection (BSI) was 0.811. In multivariate analysis, the inability to decrease PCT by more than 80% within 5–7 days after the onset of fever independently predicted poor 100-day survival following allo-HSCT (P = 0.036). Furthermore, the prognostic nomogram combining PCTc and clinical parameters showed a stable predictive performance, supported by the C-index of 0.808 and AUC of 0.813 in the primary cohort, and C-index of 0.691 and AUC of 0.697 in the validation cohort. This study demonstrated the diagnostic role of PCT in documented and bloodstream infection during the neutropenic period after allo-HSCT. PCTc might serve as a predictive indicator of post-HSCT 100-day mortality. A nomogram based on PCTc and several clinical factors effectively predicted the 100-day survival of febrile patients and may help physicians identify high-risk patients in the post-HSCT neutropenic period.

History and Development of Autologous Stem Cell Transplantation for Acute Myeloid Leukemia

This review describes the development of cryopreservation, the birth of autologous stem cell transplantation (ASCT) and its past and present use to consolidate adult patients with acute myelogenous leukemia (AML). It summarizes the first autografts in patients in relapse, the experience of autografting in complete remission (CR), using bone marrow unpurged or purged in vitro with cyclophosphamide-derivatives, and the important shift to peripheral blood stem cells. The review also discusses the results of recent studies in favor of the use of ASCT to consolidate good- and intermediate-risk patients who reach CR with no detectable minimal residual disease, and those which support the inclusion of maintenance therapy post autograft with hypomethylating agents, anti-BCL-2, and, possibly, in the future, anti AML chimeric antigen receptor-T cells. Carefully applied to well-selected patients, ASCT may regain interest, because of its simplicity, its reduced toxicity, lower non-relapse mortality and better quality of life.

Circulating Plasma Cells as a Biomarker to Predict Newly Diagnosed Multiple Myeloma Prognosis: Developing Nomogram Prognostic Models

Background: To investigate the prognostic value of circulating plasma cells (CPC) and establish novel nomograms to predict individual progression-free survival (PFS) as well as overall survival (OS) of patients with newly diagnosed multiple myeloma (NDMM).

Methods: One hundred ninetyone NDMM patients in Wuhan Union Hospital from 2017.10 to 2020.8 were included in the study. The entire cohort was randomly divided into a training (n = 130) and a validation cohort (n = 61). Univariate and multivariate analyses were performed on the training cohort to establish nomograms for the prediction of survival outcomes, and the nomograms were validated by calibration curves.

Results: When the cut-off value was 0.038%, CPC could well distinguish patients with higher tumor burden and lower response rates (P < 0.05), and could be used as an independent predictor of PFS and OS. Nomograms predicting PFS and OS were developed according to CPC, lactate dehydrogenase (LDH) and creatinine. The C-index and the area under receiver operating characteristic curves (AUC) of the nomograms showed excellent individually predictive effects in training cohort, validation cohort or entire cohort. Patients with total points of the nomograms ≤ 60.7 for PFS and 75.8 for OS could be defined as low-risk group and the remaining as high-risk group. The 2-year PFS and OS rates of patients in low-risk group was significantly higher than those in high-risk group (p < 0.001).

Conclusions: CPC is an independent prognostic factor for NDMM patients. The proposed nomograms could provide individualized PFS and OS prediction and risk stratification.

Development and validation of a prognostic model for adult patients with acute myeloid leukaemia

Background

The high heterogeneity of acute myeloid leukaemia (AML) reflected in the patient- and disease-related factors accounts for the unsatisfactory prognosis despite the introduction of novel therapeutic approaches and drugs in recent years.

Methods

In the development set (n = 412), parameters including age, hematopoietic cell transplantation-comorbidity index, white blood cell count, hemoglobin, biallelic CEBPA mutations, DNMT3A mutations, FLT3-ITD/NPM1 status, and ELN cytogenetic risk status were identified as independent prognostic factors for overall survival (OS) in the multivariable Cox regression analysis. A nomogram combining these predictors for individual risk estimation was established thereby.

Findings

The prognostic model demonstrated promising performance in the development cohort. The calibration plot, C-index (0.74), along with the 1-, 2- and 3-year area under the receiver operating characteristic curve (AUC, 0.76, 0.79, and 0.74, respectively) in the validation set (n = 238) substantiated the robustness of the model. In addition to stratifying young (age ≤ 60 years) and elderly patients (age > 60 years) into three and two risk groups with significant distinct outcomes, the prognostic model succeeded in distinguishing eligible candidates for hematopoietic stem cell transplantation.

Interpretation

The prognostic model is capable of survival prediction, risk stratification and helping with therapeutic decision-making with the use of easily acquired variables in daily clinical routine.

Funding

This work was supported in part by grants from the National Natural Science Foundation of China (81770141), the National Key R&D Program of China (2016YFE0202800), and Shanghai Municipal Education Commission-Gaofeng Clinical Medicine Grant Support (20161406).

The EBMT activity survey on hematopoietic-cell transplantation and cellular therapy 2018: CAR-T's come into focus

Hematopoietic-cell transplantation (HCT) is widely used for acquired and congenital disorders of the hematopoietic system. Number of transplants performed in Europe and associated countries continues to rise with 47,468 HCT in 42,901 patients [19,630 allogeneic (41%) and 27,838 autologous (59%)] reported by 701 centers in 50 countries in 2018. Main indications were myeloid malignancies 10,679 (25%; 97% allogeneic), lymphoid malignancies 27,318 (64%; 20% allogeneic), solid tumors 1625 (4%; 2.9% allogeneic), and nonmalignant disorders 3063 (7%; 81% allogeneic). This year's analysis focuses on cellular therapies with the marked growth in CAR T-cell therapies from 151 in 2017 to 301 patients reported in 2018. Other cellular therapy numbers show less significant changes. Important trends in HCT include a 49% increase in allogeneic HCT for chronic phase CML (although transplant numbers remain low) and a 24% increase in aplastic anemia. In autologous HCT, there is an ongoing increase in autoimmune diseases (by 19%), predominantly due to activity in multiple sclerosis. This annual report reflects current activity and highlights important trends, useful for health care planning.

Risk stratification using FLT3 and NPM1 in acute myeloid leukemia patients autografted in first complete remission

FLT3-ITD and NPM1 mutation refine prognostic stratification in acute myeloid leukemia (AML) with intermediate-risk cytogenetics. However, data on their role in patients undergoing autologous stem cell transplantation (Auto-SCT) as post-remission therapy (PRT) are limited. We therefore sought to retrospectively evaluate the role of FLT3-ITD and NPM1 in a cohort of AML patients (n = 405) with intermediate-risk cytogenetics, autografted in first complete remission (CR1). Patients were transplanted between 2000 and 2014 and reported to the European Society for Blood and Marrow Transplantation (EBMT) registry. Leukemia-free survival (LFS) was the primary outcome. Median follow-up was 5.5 years. FLT3-ITD^neg/NPM1^WT was the leading molecular subtype (50%), followed by FLT3-ITD^neg/NPM1^mut (30%). In the univariate analysis, molecular subtype was associated with LFS, overall survival (OS), and relapse incidence (RI) (p < 0.001); 5-year LFS: FLT3-ITD^neg/NPM1^mut 62%, FLT3-ITD^pos/NPM1^mut 38%, FLT3-ITD^neg/NPM1^WT 32%, and FLT3-ITD^pos/NPM1^WT 21%. At 5 years, OS and RI in the FLT3-ITD^neg/NPM1^mut subtype were 74% and 35%, respectively. The corresponding OS and RI in other subtypes were below 48% and over 57%. In a Cox multivariable model, molecular subtype was the strongest predictor of LFS, OS, and relapse. In conclusion, AML patients with intermediate-risk cytogenetics and FLT3-ITD^neg/NPM1^mut experience favorable outcomes when autografted in CR1, suggesting that Auto-SCT is a valid PRT option.

Development and validation of a preoperative nomogram for predicting survival of patients with locally advanced prostate cancer after radical prostatectomy

Background

For selected locally advanced prostate cancer (PCa) patients, radical prostatectomy (RP) is one of the first-line treatments. We aimed to develop a preoperative nomogram to identify what kinds of patients can get the most survival benefits after RP.

Methods

We conducted analyses with data from the Surveillance, Epidemiology, and End Results (SEER) database. Covariates used for analyses included age at diagnosis, marital status, race, American Joint Committee on Cancer (AJCC) 7th TNM stage, Prostate specific antigen, Gleason biopsy score (GS), percent of positive cores. We estimated the cumulative incidence function for cause-specific death. The Fine and Gray’s proportional subdistribution hazard approach was used to perform multivariable competing risk analyses and reveal prognostic factors. A nomogram was built by these factors (including GS, percent of positive cores and N stage) and validated by concordance index and calibration curves. Risk stratification was established based on the nomogram.

Results

We studied 14,185 patients. N stage, GS, and percent of positive cores were the independent prognostic factors used to construct the nomogram. For validating, in the training cohort, the C-index was 0.779 (95% CI 0.736–0.822), and in the validation cohort, the C-index was 0.773 (95% CI 0.710–0.836). Calibration curves showed that the predicted survival and actual survival were very close. The nomogram performed better over the AJCC staging system (C-index 0.779 versus 0.764 for training cohort, and 0.773 versus 0.744 for validation cohort). The new stratification of risk groups based on the nomogram also showed better discrimination than the AJCC staging system.

Conclusions

The preoperative nomogram can provide favorable prognosis stratification ability to help clinicians identify patients who are suitable for surgery.

Is There Still a Role for Autologous Stem Cell Transplantation for the Treatment of Acute Myeloid Leukemia?

After intensive induction chemotherapy and complete remission achievement, patients with acute myeloid leukemia (AML) are candidates to receive either high-dose cytarabine-based regimens, or autologous (ASCT) or allogeneic (allo-SCT) hematopoietic stem cell transplantations as consolidation treatment. Pretreatment risk classification represents a determinant key of type and intensity of post-remission therapy. Current evidence indicates that allo-SCT represents the treatment of choice for high and intermediate risk patients if clinically eligible, and its use is favored by increasing availability of unrelated or haploidentical donors. On the contrary, the adoption of ASCT is progressively declining, although numerous studies indicate that in favorable risk AML the relapse rate is lower after ASCT than chemotherapy. In addition, the burden of supportive therapy and hospitalization favors ASCT. In this review, we summarize current indications (if any) to ASCT on the basis of molecular genetics at diagnosis and minimal residual disease evaluation after induction/consolidation phase. Finally, we critically discuss the role of ASCT in older patients with AML and acute promyelocytic leukemia.

Comprehensive analysis the potential biomarkers for the high-risk of childhood acute myeloid leukemia based on a competing endogenous RNA network

Acute myeloid leukemia (AML) is a common form of hematological malignancies, the discovery of non-coding RNA (ncRNA) plays an important role in diverse biological processes including hematopoietic differentiation and proliferation. However, the interaction mechanism of key RNAs and their regulatory network in childhood AML are still to be elucidated. RNA profiles were downloaded from the Therapeutically Applicable Research to Generate Effective Treatment (TARGET) database and identified specific lncRNAs, miRNAs, and mRNAs in high-risk group of childhood AML. A lncRNA-mRNA-miRNA ceRNA network in childhood AML was constructed. A total of 2064 mRNAs, 615 lncRNAs, and 60 miRNAs were identified as significantly differentially expressed, and 13 lncRNAs, 7 miRNAs, and 67 mRNAs were incorporated in the ceRNA network. Functional analysis showed that these DEmRNAs were significantly enriched in Ras signaling pathway, TGF-beta signaling pathway, and other tumor-related pathways. Among the network, 10 RNAs (LINC00471, hsa-mir-100, hsa-mir-150, ANP32E, ERMP1, MYO1B, PAPD7, PTGIS, TERF1, and VEGFA) was associated with high-risk group of childhood AML and functions were significant for prognosis. Then, these findings together provide a new insight into the pathogenesis of high-risk group of childhood AML that can assist clinicians clarify the function of lncRNA to guide the treatment and in-depth study.