mstate: An R Package for the Analysis of Competing Risks and Multi-State Models

Multi-state models are a very useful tool to answer a wide range of questions in survival analysis that cannot, or only in a more complicated way, be answered by classical models. They are suitable for both biomedical and other applications in which time-to-event variables are analyzed. However, they are still not frequently applied. So far, an important reason for this has been the lack of available software. To overcome this problem, we have developed the mstate package in R for the analysis of multi-state models. The package covers all steps of the analysis of multi-state models, from model building and data preparation to estimation and graphical representation of the results. It can be applied to non- and semi-parametric (Cox) models. The package is also suitable for competing risks models, as they are a special category of multi-state models. This article offers guidelines for the actual use of the software by means of an elaborate multi-state analysis of data describing post-transplant events of patients with blood cancer. The data have been provided by the EBMT (the European Group for Blood and Marrow Transplantation). Special attention will be paid to the modeling of different covariate effects (the same for all transitions or transition-specific) and different baseline hazard assumptions (different for all transitions or equal for some).

Willingness to undergo surgery again validated clinically important differences in health-related quality of life after total hip replacement or total knee replacement surgery

AbstractObjectivesTo determine clinically important differences (CIDs) in health-related quality of life (HRQoL) after total hip replacement (THR) or total knee replacement (TKR) surgery, using the Short Form 36 (SF-36).Study Design and SettingSF-36 scores were collected 2 weeks before and at 1.5–6 years after joint replacement in 586 THR and 400 TKR patients in a multicenter cohort study. We calculated distribution-based CIDs (0.8 standard deviations of the preoperative score) for each SF-36 subscale. Responders (patients with an improvement in HRQoL ≥ CID of a particular subscale) were compared with nonresponders using an external validation question: willingness to undergo surgery again.ResultsCIDs for THR/TKR were physical functioning (PF), 17.9/16.7; role-physical (RP), 31.1/33.4; bodily pain (BP), 16.8/16.2; general health, 15.5/15.7; vitality, 17.3/16.7; social functioning (SF), 22.0/19.9; role-emotional, 33.7/33.6; and mental health, 14.8/14.1. CIDs of PF, RP, BP, and SF were validated by the validation question.ConclusionValid and precise CIDs are estimated of PF, RP, BP, and SF, which are relevant in HRQoL subscales for THR and TKR patients. CIDs of all other subscales should be used cautiously

SUrvival Control Chart EStimation Software in R: the success package

Monitoring the quality of statistical processes has been of great importance, mostly in industrial applications. Control charts are widely used for this purpose, but often lack the possibility to monitor survival outcomes. Recently, inspecting survival outcomes has become of interest, especially in medical settings where outcomes often depend on risk factors of patients. For this reason many new survival control charts have been devised and existing ones have been extended to incorporate survival outcomes. The R package success allows users to construct risk-adjusted control charts for survival data. Functions to determine control chart parameters are included, which can be used even without expert knowledge on the subject of control charts. The package allows to create static as well as interactive charts, which are built using ggplot2 (Wickham 2016) and plotly (Sievert 2020).Comment: 29 pages, 10 figures, guide for the R package success, see https://cran.r-project.org/package=succes

Body composition of patients with neuroblastoma using computed tomography

Background: Computed tomography (CT) is often used to investigate muscle and fat mass in adult patients with cancer. However, this method has rarely been used in the pediatric cancer population. The present retrospective study aimed to investigate changes in body composition using CT during treatment in children with neuroblastoma. Procedure: CT images of 29 patients with high-risk neuroblastoma were retrospectively analyzed at diagnosis and longitudinally during treatment. The cross-sectional area of skeletal muscle, intermuscular adipose tissue (IMAT), visceral adipose tissue (VAT), and subcutaneous adipose tissue (SAT) and skeletal muscle density at the level of the third lumbar vertebra were examined. To correct for height, cross-sectional areas were divided by height in meters squared. A linear mixed model was estimated to investigate changes in body composition over time. Results: A small increase in skeletal muscle (p =.029), skeletal muscle density (p =.002), and IMAT (p <.001) was found. Furthermore, a rapid increase in VAT (p <.001) and SAT (p =.001) was seen early during treatment with the highest volumes after six cycles of chemotherapy. Conclusions: CT scans obtained during standard care provide insight into the direction and timing of changes in skeletal muscle and different types of adipose tissue in childhood cancer patients. Future research is needed regarding the consequences of the rapid increase of VAT and SAT early during treatment

Smell and taste function in childhood cancer patients:a feasibility study

Purpose Chemotherapy can affect smell and taste function. This has never been investigated in childhood cancer patients during chemotherapy. The objective of this study was to determine whether psychophysical smell and taste tests are suitable for children with cancer. Taste and smell function, fungiform papillae density, and eating behavior were measured before (T1) and after (T2) a cycle of chemotherapy and compared with healthy controls. Methods Thirty-one childhood cancer patients treated for a hematological, solid, or brain malignancy (median age 12 years, 16 girls), and 24 healthy controls (median age: 11 years, 10 girls) participated. Smell function was measured using Sniffin' Sticks, including a threshold, discrimination, and identification test. Taste Strips were used to determine recognition thresholds for sweet, sour, salty, and bitter taste. Papillae density was investigated by counting the fungiform papillae of the anterior tongue. Eating behavior was assessed using the Behavioral Pediatrics Feeding Assessment Scale (BPFAS). Results Smell and taste function could be investigated in more than 90% of the patients, while fungiform papillae density could be determined in 61% of the patients. A significant difference in smell threshold was found between patients and controls (p = 0.001), showing lower thresholds in patients. In patients, sweet taste (p <0.001), bitter taste (p = 0.028), and total taste function (p = 0.004) were significantly different after a cycle of chemotherapy, with higher scores at T2. Conclusion The assessment of smell, taste, and fungiform papillae density is feasible in children with cancer. Results of the current study suggest that smell and taste sensitivity increased in children with cancer

Inspecting the quality of care:a comparison of CUSUM methods for inter hospital performance

During the past 14 years, a clinical audit has been used in the Netherlands to provide hospitals with data on their performance in colorectal cancer care. Continuous feedback on the quality of care provided at each hospital is essential to improve patient outcomes. It is unclear which methods should be used to generate most informative output for the identification of potential quality issues. Our aim is to compare the commonly employed funnel plot with existing cumulative sum (CUSUM) methodology for the evaluation of postoperative survival and hospital stay outcomes of patients who underwent colorectal surgery in the Netherlands. Data from the Dutch ColoRectal Audit on 25367 patients in the Netherlands who underwent surgical resection for colorectal cancer in 71 hospitals between 2019 and 2021 is used to compare four methods for the detection of deviations in the quality of care. Two methods based on binary outcomes (funnel plot, binary CUSUM) and two CUSUM charts based on survival outcomes (BK-CUSUM and CGR-CUSUM) are considered. A novel approach for determining hospital specific control limits for CUSUM charts is proposed. The ability to detect deviations as well as the time until detection are compared for the four methods. Charts were constructed for the inspection of both postoperative survival and hospital stay. Methods using survival outcomes always yielded faster detection times compared to approaches employing binary outcomes. Detections between methods mostly coincided for postoperative survival. For hospital stay detections varied strongly, with methods based on survival outcomes signalling over half the hospitals. Further pros and cons as well as pitfalls of all methods under consideration are discussed. Methodology for the continuous inspection of the quality of care should be tailored to the specific outcome. Properly understanding how the mechanism of a control chart functions is crucial for the correct interpretation of results. This is particularly true for CUSUM charts, which require the choice of a parameter that greatly influences the results. When applying CUSUM charts, consideration of these issues is strongly recommended.</p

A multicenter, prospective cohort study

Organ transplant recipients (OTRs) have a 100‐fold increased risk of cutaneous squamous cell carcinoma (cSCC). We prospectively evaluated the association between β genus human papillomaviruses (βPV) and keratinocyte carcinoma in OTRs. Two OTR cohorts without cSCC were assembled: cohort 1 was transplanted in 2003‐2006 (n = 274) and cohort 2 was transplanted in 1986‐2002 (n = 352). Participants were followed until death or cessation of follow‐up in 2016. βPV infection was assessed in eyebrow hair by using polymerase chain reaction–based methods. βPV IgG seroresponses were determined with multiplex serology. A competing risk model with delayed entry was used to estimate cumulative incidence of histologically proven cSCC and the effect of βPV by using a multivariable Cox regression model. Results are reported as adjusted hazard ratios (HRs). OTRs with 5 or more different βPV types in eyebrow hair had 1.7 times the risk of cSCC vs OTRs with 0 to 4 different types (HR 1.7, 95% confidence interval 1.1‐2.6). A similar risk was seen with high βPV loads (HR 1.8, 95% confidence interval 1.2‐2.8). No significant associations were seen between serum antibodies and cSCC or between βPV and basal cell carcinoma. The diversity and load of βPV types in eyebrow hair are associated with cSCC risk in OTRs, providing evidence that βPV is associated with cSCC carcinogenesis and may present a target for future preventive strategies

Prognostic factors for multi-organ dysfunction in pediatric oncology patients admitted to the pediatric intensive care unit

Background: Pediatric oncology patients who require admission to the pediatric intensive care unit (PICU) have worse outcomes compared to their non-cancer peers. Although multi-organ dysfunction (MOD) plays a pivotal role in PICU mortality and morbidity, risk factors for MOD have not yet been identified. We aimed to identify risk factors at PICU admission for new or progressive MOD (NPMOD) during the first week of PICU stay.Methods: This retrospective cohort study included all pediatric oncology patients aged 0 to 18 years admitted to the PICU between June 2018 and June 2021. We used the recently published PODIUM criteria for defining multi-organ dysfunction and estimated the association between covariates at PICU baseline and the outcome NPMOD using a multivariable logistic regression model, with PICU admission as unit of study. To study the predictive performance, the model was internally validated by using bootstrap.Results: A total of 761 PICU admissions of 571 patients were included. NPMOD was present in 154 PICU admissions (20%). Patients with NPMOD had a high mortality compared to patients without NPMOD, 14% and 1.0% respectively. Hemato-oncological diagnosis, number of failing organs and unplanned admission were independent risk factors for NPMOD. The prognostic model had an overall good discrimination and calibration.Conclusion: The risk factors at PICU admission for NPMOD may help to identify patients who may benefit from closer monitoring and early interventions. When applying the PODIUM criteria, we found some opportunities for fine-tuning these criteria for pediatric oncology patients, that need to be validated in future studies.</p

Prognostic factors for multi-organ dysfunction in pediatric oncology patients admitted to the pediatric intensive care unit

Background: Pediatric oncology patients who require admission to the pediatric intensive care unit (PICU) have worse outcomes compared to their non-cancer peers. Although multi-organ dysfunction (MOD) plays a pivotal role in PICU mortality and morbidity, risk factors for MOD have not yet been identified. We aimed to identify risk factors at PICU admission for new or progressive MOD (NPMOD) during the first week of PICU stay.Methods: This retrospective cohort study included all pediatric oncology patients aged 0 to 18 years admitted to the PICU between June 2018 and June 2021. We used the recently published PODIUM criteria for defining multi-organ dysfunction and estimated the association between covariates at PICU baseline and the outcome NPMOD using a multivariable logistic regression model, with PICU admission as unit of study. To study the predictive performance, the model was internally validated by using bootstrap.Results: A total of 761 PICU admissions of 571 patients were included. NPMOD was present in 154 PICU admissions (20%). Patients with NPMOD had a high mortality compared to patients without NPMOD, 14% and 1.0% respectively. Hemato-oncological diagnosis, number of failing organs and unplanned admission were independent risk factors for NPMOD. The prognostic model had an overall good discrimination and calibration.Conclusion: The risk factors at PICU admission for NPMOD may help to identify patients who may benefit from closer monitoring and early interventions. When applying the PODIUM criteria, we found some opportunities for fine-tuning these criteria for pediatric oncology patients, that need to be validated in future studies.</p

Prognostic factors for multi-organ dysfunction in pediatric oncology patients admitted to the pediatric intensive care unit

Background: Pediatric oncology patients who require admission to the pediatric intensive care unit (PICU) have worse outcomes compared to their non-cancer peers. Although multi-organ dysfunction (MOD) plays a pivotal role in PICU mortality and morbidity, risk factors for MOD have not yet been identified. We aimed to identify risk factors at PICU admission for new or progressive MOD (NPMOD) during the first week of PICU stay.Methods: This retrospective cohort study included all pediatric oncology patients aged 0 to 18 years admitted to the PICU between June 2018 and June 2021. We used the recently published PODIUM criteria for defining multi-organ dysfunction and estimated the association between covariates at PICU baseline and the outcome NPMOD using a multivariable logistic regression model, with PICU admission as unit of study. To study the predictive performance, the model was internally validated by using bootstrap.Results: A total of 761 PICU admissions of 571 patients were included. NPMOD was present in 154 PICU admissions (20%). Patients with NPMOD had a high mortality compared to patients without NPMOD, 14% and 1.0% respectively. Hemato-oncological diagnosis, number of failing organs and unplanned admission were independent risk factors for NPMOD. The prognostic model had an overall good discrimination and calibration.Conclusion: The risk factors at PICU admission for NPMOD may help to identify patients who may benefit from closer monitoring and early interventions. When applying the PODIUM criteria, we found some opportunities for fine-tuning these criteria for pediatric oncology patients, that need to be validated in future studies.</p