scholarly journals Association of pre-existing comorbidities with outcome of allogeneic hematopoietic cell transplantation. A retrospective analysis from the EBMT

2021 ◽  
Author(s):  
Olaf Penack ◽  
Christophe Peczynski ◽  
Mohamad Mohty ◽  
Ibrahim Yakoub-Agha ◽  
Rafael de la Camara ◽  
...  
Keyword(s):  
Cell Transplantation ◽  
Hematopoietic Cell Transplantation ◽  
Proportional Hazards ◽  
Proportional Hazards Model ◽  
Cox Proportional Hazards ◽  
Cox Proportional Hazards Model ◽  
Hematopoietic Cell ◽  
Allogeneic Hematopoietic Cell Transplantation ◽  
Full Data ◽  
Data Set

AbstractRisk assessment of allogeneic hematopoietic cell transplantation (allo-HCT) is hindered by the lack of current data on comorbidities and outcome. The EBMT identified 38,760 allo-HCT recipients with hematologic malignancies transplanted between 2010 and 2018 from matched sibling and unrelated donors with a full data set of pre-existing comorbidities. Multivariate analyses using the Cox proportional-hazards model including known risk factors for non-relapse mortality (NRM) were performed. We found that pre-existing renal comorbidity had the strongest association with NRM (hazard ratio [HR] 1.85 [95% CI 1.55–2.19]). In addition, the association of multiple pre-existing comorbidities with NRM was significant, including diabetes, infections, cardiac comorbidity, and pulmonary comorbidity. However, the HR of the association of these comorbidities with NRM was relatively low and did not exceed 1.24. Consequently, the risk of NRM was only moderately increased in patients with a high hematopoietic cell transplantation comorbidity index (HCT-CI) ≥ 3 (HR 1.34 [1.26–1.42]). In the current EBMT population, pre-existing non-renal comorbidities determined NRM after allo-HCT to a much lesser extent as compared with the underlying HCT-CI data. Improvements in management and supportive care as well as higher awareness based on the use of HCT-CI may have contributed to this favorable development.

Tandem high-dose chemotherapy and autologous hematopoietic stem cell transplantation (SCT) compared to single SCT for relapsed/refractory germ cell tumors (GCT).

2018 ◽  
Vol 36 (6_suppl) ◽  
pp. 572-572
Author(s):  
Deepak Kilari ◽  
Parameswaran Hari ◽  
Muna Qayed ◽  
Raphael Fraser ◽  
Omar Davila ◽  
...  
Keyword(s):  
Cell Transplantation ◽  
Hematopoietic Cell Transplantation ◽  
Proportional Hazards ◽  
Proportional Hazards Model ◽  
Germ Cell Tumors ◽  
Progression Free Survival ◽  
Cox Proportional Hazards ◽  
Cox Proportional Hazards Model ◽  
High Dose ◽  
Hematopoietic Stem

572 Background: Single-center observational studies have established the use of single or tandem SCT to salvage relapsed GCT but randomized trials are lacking. We analyzed outcomes and prognostic factors in 2,395 male SCT recipients for relapsed GCT between 1990 and 2015. Methods: Recipients of single or tandem SCT reported to the Center for International Blood and Marrow Transplant Research were identified. Outcomes were compared by SCT year: 1990-94 (N = 288), 1995-99 (N = 351), 2000-04 (N = 376), 2005-09 (N = 509) and 2010-15 (N = 871). A recent subset (n = 267, 2000-2015) with detailed disease- and transplant-related data was further analyzed with a multivariate (MVA) Cox proportional hazards model. Results: Median age at SCT was 31 (11-76) years and 49% received SCT within 12 months of diagnosis consistent with early relapse/primary refractory GCT. 26% had primary extragonadal GCT; 1,167 (49%) had intent to tandem transplant (TT). The median follow up was 51 (3-313) months. Day 100 non-relapse mortality was statistically similar at 8% in 1990-94 (vs. 4% in 2010-15) but 3-year progression-free survival (PFS) improved from 24 (18-31)% in 1990-94 to 47 (43-50)% in 2010-15 (p < 0.0001) and 3-year survival (OS) from 35 (29-40)% to 54 (50-57)% in 2010-15 (p < 0.0001). Compared with single SCT, TT recipients were younger 31 (16-62) vs 34 (13-76), with lower Hematopoietic Cell Transplantation-Comorbidity Index, more likely to undergo SCT after 1 line of chemotherapy (28% vs 9%), and within 1 year of diagnosis (51% vs 38%). TT was preferred over single SCT over time (48% of SCT were TT in 2000-04 vs. 81% in 2010-15). In MVA, non-seminoma histology, residual tumor at SCT, receipt of > 1 line of pre-SCT chemotherapy and single SCT (vs. TT), were associated with worse PFS and OS. Year of SCT was not significant when adjusted for these covariates. Conclusions: In this large longitudinal cohort, improvements in PFS and OS were observed in recent years. SCT earlier in disease course and tandem SCT were associated with superior outcomes. These data involving a large cohort reported from 225 centers confirm specialized centers’ date in a real-world setting.

scholarly journals Increased risk of breast cancer among survivors of allogeneic hematopoietic cell transplantation: a report from the FHCRC and the EBMT-Late Effect Working Party

Blood ◽  
2008 ◽  
Vol 111 (2) ◽  
pp. 939-944 ◽  
Author(s):  
Debra L. Friedman ◽  
Alicia Rovo ◽  
Wendy Leisenring ◽  
Anna Locasciulli ◽  
Mary E. D. Flowers ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Cell Transplantation ◽  
Hematopoietic Cell Transplantation ◽  
Proportional Hazards Model ◽  
Multivariable Analysis ◽  
Working Party ◽  
Cox Proportional Hazards Model ◽  
Hematopoietic Cell ◽  
Allogeneic Hematopoietic Cell Transplantation ◽  
Increased Risk

As risk for secondary breast cancer is elevated among cancer survivors treated with conventional therapy, we sought to determine the risk among 3337 female 5-year survivors who underwent an allogeneic hematopoietic cell transplantation (HCT) at the Fred Hutchinson Cancer Research Center or at one of 82 centers reporting to the European Bone Marrow Transplant Registry. Risk was calculated using standardized incidence ratios (SIRs), and risk factors were evaluated with a multivariable Cox proportional hazards model. Fifty-two survivors developed breast cancer at a median of 12.5 (range: 5.7-24.8) years following HCT (SIR = 2.2). Twenty-five–year cumulative incidence was 11.0%, higher among survivors who received total body irradiation (TBI) (17%) than those who did not receive TBI (3%). In multivariable analysis, increased risk was associated with longer time since transplantation (hazard ratio [HR] for 20+ years after transplantation = 10.8), use of TBI (HR = 4.0), and younger age at transplantation (HR = 9.5 for HCT < 18 years). Hazard for death associated with breast cancer was 2.5 (95% CI: 1.1-5.8). We conclude that female survivors of allogeneic HCT are at increased risk of breast cancer and should be educated about the need for regular screening.

Age at Exposure to Parental Suicide and the Subsequent Risk of Suicide in Young People

Crisis ◽  
2018 ◽  
Vol 39 (1) ◽  
pp. 27-36 ◽  
Author(s):  
Kuan-Ying Lee ◽  
Chung-Yi Li ◽  
Kun-Chia Chang ◽  
Tsung-Hsueh Lu ◽  
Ying-Yeh Chen
Keyword(s):  
Young People ◽  
Proportional Hazards ◽  
Proportional Hazards Model ◽  
Cox Proportional Hazards ◽  
Cox Proportional Hazards Model ◽  
Birth Registry ◽  
Data Set ◽  
Parental Suicide ◽  
The Impact ◽  
Age At Exposure

Abstract. Background: We investigated the age at exposure to parental suicide and the risk of subsequent suicide completion in young people. The impact of parental and offspring sex was also examined. Method: Using a cohort study design, we linked Taiwan's Birth Registry (1978–1997) with Taiwan's Death Registry (1985–2009) and identified 40,249 children who had experienced maternal suicide (n = 14,431), paternal suicide (n = 26,887), or the suicide of both parents (n = 281). Each exposed child was matched to 10 children of the same sex and birth year whose parents were still alive. This yielded a total of 398,081 children for our non-exposed cohort. A Cox proportional hazards model was used to compare the suicide risk of the exposed and non-exposed groups. Results: Compared with the non-exposed group, offspring who were exposed to parental suicide were 3.91 times (95% confidence interval [CI] = 3.10–4.92 more likely to die by suicide after adjusting for baseline characteristics. The risk of suicide seemed to be lower in older male offspring (HR = 3.94, 95% CI = 2.57–6.06), but higher in older female offspring (HR = 5.30, 95% CI = 3.05–9.22). Stratified analyses based on parental sex revealed similar patterns as the combined analysis. Limitations: As only register-­based data were used, we were not able to explore the impact of variables not contained in the data set, such as the role of mental illness. Conclusion: Our findings suggest a prominent elevation in the risk of suicide among offspring who lost their parents to suicide. The risk elevation differed according to the sex of the afflicted offspring as well as to their age at exposure.

Development and validation of a pediatric disease risk index for allogeneic hematopoietic cell transplantation.

2020 ◽  
Vol 38 (15_suppl) ◽  
pp. 7503-7503
Author(s):  
Muna Qayed ◽  
Carrie L Kitko ◽  
Kwang Woo Ahn ◽  
Mariam H Johnson ◽  
Kirk R. Schultz ◽  
...  
Keyword(s):  
High Risk ◽  
Hematopoietic Cell Transplantation ◽  
Proportional Hazards ◽  
Proportional Hazards Model ◽  
Disease Risk ◽  
Risk Index ◽  
Risk Groups ◽  
The United States ◽  
Cox Proportional Hazards ◽  
Cox Proportional Hazards Model

7503 Background: Characteristics such as disease, disease status and cytogenetic abnormalities impact relapse and survival after transplantation for acute myeloid (AML) and acute lymphoblastic (ALL) leukemia. In adults, these attributes were used to derive the disease risk index for survival. Thus, the current analysis sought to develop and validate a pediatric disease risk index (p-DRI). Methods: Eligible were patients aged <18 years with AML (n=1135) and ALL (n=1228) transplanted between 2008 and 2017 in the United States. Separate analyses were performed for AML and ALL. Patients were randomly assigned (1:1) to a training and validation cohort. Cox proportional hazards model with stepwise selection was used to select significant variables (2-sided p<0.05). The primary outcome was leukemia-free survival (LFS; relapse or death were events). Based on the magnitude of log(HR), a weighted score was assigned to each characteristic that met the level of significance and risk groups were created. Results: Four risk groups were identified for AML and three risk groups for ALL (Table). The 5-year probabilities of LFS for AML were 81% (68-91), 56% (51-61), 44% (39-49) and 21% (15-28) for good, intermediate, high and very high-risk groups, respectively. The 5-year probabilities of LFS for ALL were 68% (63-72), 50% (45-54) and 15% (3-34) for good, intermediate, high risk groups, respectively. Conclusions: This validated p-DRI successfully stratified children with AML and ALL for prognostication undergoing allogeneic transplantation. [Table: see text]

scholarly journals Hematopoietic Cell Transplantation–Specific Comorbidity Index Predicts Inpatient Mortality and Survival in Patients Who Received Allogeneic Transplantation Admitted to the Intensive Care Unit

2013 ◽  
Vol 31 (33) ◽  
pp. 4207-4214 ◽  
Author(s):  
Ulas D. Bayraktar ◽  
Elizabeth J. Shpall ◽  
Ping Liu ◽  
Stefan O. Ciurea ◽  
Gabriela Rondon ◽  
...  
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
Cell Transplantation ◽  
Hematopoietic Cell Transplantation ◽  
Proportional Hazards ◽  
Cox Proportional Hazards ◽  
Hematopoietic Cell ◽  
Inpatient Mortality ◽  
Icu Admission ◽  
Comorbidity Index

Purpose To investigate the prognostic value of the Hematopoietic Cell Transplantation–Specific Comorbidity Index (HCT-CI) in patients who received transplantation admitted to the intensive care unit (ICU). Patients and Methods We investigated the association of HCT-CI with inpatient mortality and overall survival (OS) among 377 patients who were admitted to the ICU within 100 days of allogeneic stem-cell transplantation (ASCT) at our institution. HCT-CI scores were collapsed into four groups and were evaluated in univariate and multivariate analyses using logistic regression and Cox proportional hazards models. Results The most common pretransplantation comorbidities were pulmonary and cardiac diseases, and respiratory failure was the primary reason for ICU admission. We observed a strong trend for higher inpatient mortality and shorter OS among patients with HCT-CI values ≥ 2 compared with patients with values of 0 to 1 in all patient subsets studied. Multivariate analysis showed that patients with HCT-CI values ≥ 2 had significantly higher inpatient mortality than patients with values of 0 to 1 and that HCT-CI values ≥ 4 were significantly associated with shorter OS compared with values of 0 to 1 (hazard ratio, 1.74; 95% CI, 1.23 to 2.47). The factors associated with lower inpatient mortality were ICU admission during the ASCT conditioning phase or the use of reduced-intensity conditioning regimens. The overall inpatient mortality rate was 64%, and the 1-year OS rate was 15%. Among patients with HCT-CI scores of 0 to 1, 2, 3, and ≥ 4, the 1-year OS rates were 22%, 17%, 18%, and 9%, respectively. Conclusion HCT-CI is a valuable predictor of mortality and survival in critically ill patients after ASCT.

scholarly journals Pathway-Based Personalized Analysis of Pan-Cancer Transcriptomic Data

Biomedicines ◽  
2021 ◽  
Vol 9 (11) ◽  
pp. 1502
Author(s):  
Cong Pian ◽  
Mengyuan He ◽  
Yuanyuan Chen
Keyword(s):  
Proportional Hazards ◽  
Proportional Hazards Model ◽  
Cox Proportional Hazards ◽  
Cox Proportional Hazards Model ◽  
The Cancer Genome Atlas ◽  
Data Set ◽  
Transcriptomic Data ◽  
Cancer Types ◽  
The Individual ◽  
Pathway Deregulation

The occurrence of cancer is closely related to the deregulation of certain pathways. Based on pathway deregulation scores (PDS) inferred by the Pathifier algorithm, we analyzed transcriptomic data of 13 different cancer types in The Cancer Genome Atlas database to identify cancer-specific deregulated pathways and prognostic pathways. The results showed that the individual-specific pathway deregulation scores can clearly distinguish different cancer types and their tumor-adjacent tissues. In addition, the cancer-specific deregulated pathways and prognostic pathways of different cancer types had high heterogeneity, and the identified cancer prognostic pathways have been reported to be closely related to the corresponding cancers. Furthermore, we also found that cancers with more deregulation pathways tend to be malignant and have worse prognoses. Finally, a Cox proportional Hazards model was constructed based on the prognostic pathways; this model successfully predicted survival and prognosis based on data from cancer samples. In addition, the performance of the breast cancer prognostic model was validated with an independent data set in the METABRIC database. Therefore, the prognostic pathways we identified have the potential to become targets for the treatment of cancer.

scholarly journals Combining Symbolic Regression with the Cox Proportional Hazards Model Improves Prediction of Heart Failure Deaths

2021 ◽  
Author(s):  
Casper Wilstrup ◽  
Chris Cave
Keyword(s):  
Heart Failure ◽  
Medical Records ◽  
Proportional Hazards ◽  
Proportional Hazards Model ◽  
Cox Model ◽  
Symbolic Regression ◽  
Cox Proportional Hazards ◽  
Cox Proportional Hazards Model ◽  
Data Set ◽  
Hazards Model

Abstract Background: Heart failure is a clinical syndrome characterised by a reduced ability of the heart to pump blood. Patients with heart failure have a high mortality rate, and physicians need reliable prognostic predictions to make informed decisions about the appropriate application of devices, transplantation, medications, and palliative care. In this study, we demonstrate that combining symbolic regression with the Cox proportional hazards model improves the ability to predict death due to heart failure compared to using the Cox proportional hazards model alone. Methods: We used a newly invented symbolic regression method called the QLattice to analyse a data set of medical records for 299 Pakistani patients diagnosed with heart failure. The QLattice identified a minimal set of mathematical transformations of the available covariates, which we then used in a Cox model to predict survival.Results: An exponential function of age, the inverse of ejection fraction, and the inverse of serum creatinine were identified as the best risk factors for predicting heart failure deaths. A Cox model fitted on these transformed covariates had improved predictive performance compared with a Cox model on the same covariates without mathematical transformations. Conclusion: Symbolic regression is a way to find transformations of covariates from patients’ medical records which can improve the performance of survival regression models. At the same time, these simple functions are intuitive and easy to apply in clinical settings. The direct interpretability of the simple forms may help researchers gain new insights into the actual causal pathways leading to deaths.

scholarly journals Survival following allogeneic transplant in patients with myelofibrosis

2020 ◽  
Vol 4 (9) ◽  
pp. 1965-1973 ◽  
Author(s):  
Krisstina Gowin ◽  
Karen Ballen ◽  
Kwang Woo Ahn ◽  
Zhen-Huan Hu ◽  
Haris Ali ◽  
...  
Keyword(s):  
Hematopoietic Cell Transplantation ◽  
Proportional Hazards ◽  
Proportional Hazards Model ◽  
Cox Proportional Hazards ◽  
Cox Proportional Hazards Model ◽  
International Prognostic Scoring System ◽  
First Year ◽  
Curative Therapy ◽  
Hazards Model ◽  
The Cost

Abstract Allogeneic hematopoietic cell transplantation (HCT) is the only curative therapy for myelofibrosis (MF). In this large multicenter retrospective study, overall survival (OS) in MF patients treated with allogeneic HCT (551 patients) and without HCT (non-HCT) (1377 patients) was analyzed with Cox proportional hazards model. Survival analysis stratified by the Dynamic International Prognostic Scoring System (DIPSS) revealed that the first year of treatment arm assignment, due to upfront risk of transplant-related mortality (TRM), HCT was associated with inferior OS compared with non-HCT (non-HCT vs HCT: DIPSS intermediate 1 [Int-1]: hazard ratio [HR] = 0.26, P &lt; .0001; DIPSS-Int-2 and higher: HR, 0.39, P &lt; .0001). Similarly, in the DIPSS low-risk MF group, due to upfront TRM risk, OS was superior with non-HCT therapies compared with HCT in the first-year post treatment arm assignment (HR, 0.16, P = .006). However, after 1 year, OS was not significantly different (HR, 1.38, P = .451). Beyond 1 year of treatment arm assignment, an OS advantage with HCT therapy in Int-1 and higher DIPSS score patients was observed (non-HCT vs HCT: DIPSS-Int-1: HR, 2.64, P &lt; .0001; DIPSS-Int-2 and higher: HR, 2.55, P &lt; .0001). In conclusion, long-term OS advantage with HCT was observed for patients with Int-1 or higher risk MF, but at the cost of early TRM. The magnitude of OS benefit with HCT increased as DIPSS risk score increased and became apparent with longer follow-up.

scholarly journals Estimating and Interpreting Effects from Nonlinear Exposure-Response Curves in Occupational Cohorts Using Truncated Power Basis Expansions and Penalized Splines

2017 ◽  
Vol 2017 ◽  
pp. 1-16 ◽  
Author(s):  
Elizabeth J. Malloy ◽  
Jay M. Kapellusch ◽  
Arun Garg
Keyword(s):  
Proportional Hazards ◽  
Proportional Hazards Model ◽  
Simulated Data ◽  
Cox Proportional Hazards ◽  
Cox Proportional Hazards Model ◽  
Penalized Splines ◽  
Response Curves ◽  
Data Set ◽  
Exposure Response ◽  
Power Basis

Truncated power basis expansions and penalized spline methods are demonstrated for estimating nonlinear exposure-response relationships in the Cox proportional hazards model. R code is provided for fitting models to get point and interval estimates. The method is illustrated using a simulated data set under a known exposure-response relationship and in a data application examining risk of carpal tunnel syndrome in an occupational cohort.

Methods for displaying and calibration of Cox proportional hazards models

2017 ◽  
Vol 232 (1) ◽  
pp. 105-115
Author(s):  
Chrianna I Bharat ◽  
Kevin Murray ◽  
Edward Cripps ◽  
Melinda R Hodkiewicz
Keyword(s):  
Proportional Hazards ◽  
Proportional Hazards Model ◽  
Explanatory Power ◽  
Cox Proportional Hazards ◽  
Remaining Useful Life ◽  
Cox Proportional Hazards Model ◽  
Data Set ◽  
Proportional Hazards Models ◽  
Hazards Model ◽  
Cox Proportional Hazards Models

Cox proportional hazards modelling is a widely used technique for determining relationships between observed data and the risk of asset failure when model performance is satisfactory. Cox proportional hazards models possess good explanatory power and are used by asset managers to gain insight into factors influencing asset life. However, validation of Cox proportional hazards models is not straightforward and is seldom considered in the maintenance literature. A comprehensive validation process is a necessary foundation to build trust in the failure models that underpin remaining useful life prediction. This article describes data splitting, model discrimination, misspecification and fit methods necessary to build trust in the ability of a Cox proportional hazards model to predict failures on out-of-sample assets. Specifically, we consider (1) Prognostic Index comparison for training and test sets, (2) Kaplan–Meier curves for different risk bands, (3) hazard ratios across different risk bands and (4) calibration of predictions using cross-validation. A Cox proportional hazards model on an industry data set of water pipe assets is used for illustrative purposes. Furthermore, because we are dealing with a non-statistical managerial audience, we demonstrate how graphical techniques, such as forest plots and nomograms, can be used to present prediction results in an easy to interpret way.

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