ReviewTransplantation and cellular therapy2021
Statistical Methods for Time-Dependent Variables in Hematopoietic Cell Transplantation Studies.
Review in Transplantation and cellular therapy, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
10 citing papers in PubMed, 16 citations in OpenAlex.
- Posttransplant cyclophosphamide is associated with increased cytomegalovirus infection: a CIBMTR analysis.Blood · 2021Trial
- Statistical Methods for Chimeric Antigen Receptor Cell Therapy Outcomes: A Review and Practical Considerations.Transplantation and cellular therapy · 2026Review
- Article
- Impact of fragmented care on cancer outcomes among korean women with breast and cervical cancer: a focus on regional and economic disparities.International journal for equity in health · 2025Article
- Post-transplantation cyclophosphamide is associated with increased bacterial infections.Bone marrow transplantation · 2024Article
- Incidence and Impact of Fungal Infections in Post-Transplantation Cyclophosphamide-Based Graft-versus-Host Disease Prophylaxis and Haploidentical Hematopoietic Cell Transplantation: A Center for International Blood and Marrow Transplant Research Analysis.Transplantation and cellular therapy · 2024Article
- The incidence and impact of clostridioides difficile infection on transplant outcomes in acute leukemia and MDS after allogeneic hematopoietic cell transplant-a CIBMTR study.Bone marrow transplantation · 2023Article
- Post-Transplantation Cyclophosphamide Is Associated with an Increase in Non-Cytomegalovirus Herpesvirus Infections in Patients with Acute Leukemia and Myelodysplastic Syndrome.Transplantation and cellular therapy · 2022Article
- Severe acute graft-versus-host disease increases the incidence of blood stream infection and mortality after allogeneic hematopoietic cell transplantation: Japanese transplant registry study.Bone marrow transplantation · 2021Article
- Incidence and impact of community respiratory viral infections in post-transplant cyclophosphamide-based graft-versus-host disease prophylaxis and haploidentical stem cell transplantation.British journal of haematology · 2021Article
Corrections and comments
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Authors and funding
5 authors at 2 institutions in 1 country.
Funding
Abstract
The interaction of clinically important yet time-dependent events such as infection and acute graft-versus-host disease (GVHD) on hematopoietic cell transplant outcomes is of particular interest to transplant physicians. Clinically, the development of these events is unknown at the time of transplant, but both events place the patient at risk of morbidity and mortality. Furthermore, the occurrence of one may affect the risk for the development of the other (ie, GVHD results in increased immunosuppression, resulting in infection). While these risks can be determined using traditional Cox modeling, due to their time-varying effects on the outcome, it is challenging to graphically display the patient's expected clinical status over time. Landmark analysis is one of the commonly used methods to present time-dependent variables graphically. It can be a useful tool for describing an outcome of interest with time-dependent variables. In this article, we review the basic concepts of time-dependent variables and describe a landmark study with a single-landmark time point and a dynamic landmark study with multiple landmark time points. We illustrate these methods with a hematopoietic cell transplantation data set with infections.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.