Evaluating cancer screening programs using survival analysis

The main purpose of cancer screening programs is to provide early treatment to patients that are diagnosed with cancer on a screening test, thus increasing their chances of survival. To test this hypothesis directly, one should compare the survival of screen-detected cases to the survival of their counterparts not included to the program. In this study, we develop a general notation and use it to formally define the comparison of interest. We explain why the naive comparison between screen-detected and interval cases is biased and show that the total bias that arises in this case can be decomposed as a sum of lead time bias, length time bias, and bias due to overdetection. With respect to the estimation, we show what can be estimated using existing methods. To fill in the missing gap, we develop a new nonparametric estimator that allows us to estimate the survival of the control group, that is, the survival of cancer cases that would be screen-detected among those not included to the program. By joining the proposed estimator with existing methods, we show that the contrast of interest can be estimated without neglecting any of the biases. Our approach is illustrated using simulations and empirical data.

What is relative survival and what is its role in haematology?

In many haematological diseases, the survival probability is the key outcome. However, when the population of patients is rather old and the follow-up long, a significant proportion of deaths cannot be attributed to the studied disease. This lessens the importance of common survival analysis measures like overall survival and shows the need for other outcome measures requiring more complex methodology. When disease-specific information is of interest but the cause of death is not available in the data, relative survival methodology becomes crucial. The idea of relative survival is to merge the observed data set with the mortality data in the general population and thus allow for an indirect estimation of the burden of the disease. In this work, an overview of different measures that can be of interest in the field of haematology is given. We introduce the crude mortality that reports the probability of dying due to the disease of interest; the net survival that focuses on excess hazard alone and presents the key measure in comparing the disease burden of patients from populations with different general population mortality; and the relative survival ratio which gives a simple comparison of the patients' and the general population survival. We explain the properties of each measure, and some brief notes are given on estimation. Furthermore, we describe how association with covariates can be studied. All the methods and their estimators are illustrated on a sub-cohort of older patients who received a first allogeneic hematopoietic stem cell transplantation for myelodysplastic syndromes or secondary acute myeloid leukemia, to show how different methods can provide different insights into the data.

Expected life years compared to the general population

For cohorts with long-term follow-up, the number of years lost due to a certain disease yields a measure with a simple and appealing interpretation. Recently, an overview of the methodology used for this goal has been published, and two measures have been proposed. In this work, we consider a third option that may be useful in settings in which the other two are inappropriate. In all three measures, the survival of the given dataset is compared to the expected survival in the general population which is calculated using external mortality tables. We thoroughly analyze the differences between the three measures, their assumptions, interpretation, and the corresponding estimators. The first measure is defined in a competing risk setting and assumes an excess hazard compared to the population, while the other two measures also allow estimation for groups that live better than the general population. In this case, the observed survival of the patients is compared to that in the population. The starting point of this comparison depends on whether the entry into the study is a hazard changing event (e.g., disease diagnosis or the age at which the inclusion criteria were met). Focusing on the newly defined life years difference measure, we study the estimation of the variance and consider the possible challenges (e.g., extrapolation) that occur in practice. We illustrate its use with a dataset of French Olympic athletes. Finally, an efficient R implementation has been developed for all three measures which make this work easily available to subsequent users.

Inference for transition probabilities in non-Markov multi-state models

Multi-state models are frequently used when data come from subjects observed over time and where focus is on the occurrence of events that the subjects may experience. A convenient modeling assumption is that the multi-state stochastic process is Markovian, in which case a number of methods are available when doing inference for both transition intensities and transition probabilities. The Markov assumption, however, is quite strict and may not fit actual data in a satisfactory way. Therefore, inference methods for non-Markov models are needed. In this paper, we review methods for estimating transition probabilities in such models and suggest ways of doing regression analysis based on pseudo observations. In particular, we will compare methods using land-marking with methods using plug-in. The methods are illustrated using simulations and practical examples from medical research.

Integrating relative survival in multi-state models—a non-parametric approach

Multi-state models provide an extension of the usual survival/event-history analysis setting. In the medical domain, multi-state models give the possibility of further investigating intermediate events such as relapse and remission. In this work, a further extension is proposed using relative survival, where mortality due to population causes (i.e. non-disease-related mortality) is evaluated. The objective is to split all mortality in disease and non-disease-related mortality, with and without intermediate events, in datasets where cause of death is not recorded or is uncertain. To this end, population mortality tables are integrated into the estimation process, while using the basic relative survival idea that the overall mortality hazard can be written as a sum of a population and an excess part. Hence, we propose an upgraded non-parametric approach to estimation, where population mortality is taken into account. Precise definitions and suitable estimators are given for both the transition hazards and probabilities. Variance estimating techniques and confidence intervals are introduced and the behaviour of the new method is investigated through simulations. The newly developed methodology is illustrated by the analysis of a cohort of patients followed after an allogeneic hematopoietic stem cell transplantation. The work has been implemented in the R package mstate.

Direct modeling of the crude probability of cancer death and the number of life years lost due to cancer without the need of cause of death: a pseudo-observation approach in the relative survival setting

In population-based cancer studies, net survival is a crucial measure for population comparison purposes. However, alternative measures, namely the crude probability of death (CPr) and the number of life years lost (LYL) due to death according to different causes, are useful as complementary measures for reflecting different dimensions in terms of prognosis, treatment choice, or development of a control strategy. When the cause of death (COD) information is available, both measures can be estimated in competing risks setting using either cause-specific or subdistribution hazard regression models or with the pseudo-observation approach through direct modeling. We extended the pseudo-observation approach in order to model the CPr and the LYL due to different causes when information on COD is unavailable or unreliable (i.e., in relative survival setting). In a simulation study, we assessed the performance of the proposed approach in estimating regression parameters and examined models with different link functions that can provide an easier interpretation of the parameters. We showed that the pseudo-observation approach performs well for both measures and we illustrated their use on cervical cancer data from the England population-based cancer registry. A tutorial showing how to implement the method in R software is also provided.

COVID-19 in Slovenia, from a Success Story to Disaster: What Lessons Can Be Learned?

During the first wave of the COVID-19 pandemic in spring 2020, Slovenia was among the least affected countries, but the situation became drastically worse during the second wave in autumn 2020 with high numbers of deaths per number of inhabitants, ranking Slovenia among the most affected countries. This was true even though strict non-pharmaceutical interventions (NPIs) to control the progression of the epidemic were being enforced. Using a semi-parametric Bayesian model developed for the purpose of this study, we explore if and how the changes in mobility, their timing and the activation of contact tracing can explain the differences in the epidemic progression of the two waves. To fit the model, we use data on daily numbers of deaths, patients in hospitals, intensive care units, etc., and allow transmission intensity to be affected by contact tracing and mobility (data obtained from Google Mobility Reports). Our results imply that though there is some heterogeneity not explained by mobility levels and contact tracing, implementing interventions at a similar stage as in the first wave would keep the death toll and the health system burden low in the second wave as well. On the other hand, sticking to the same timeline of interventions as observed in the second wave and focusing on enforcing a higher decrease in mobility would not be as beneficial. According to our model, the ‘dance’ strategy, i.e., first allowing the numbers to rise and then implementing strict interventions to make them drop again, has been played at too-late stages of the epidemic. In contrast, a 15–20% reduction of mobility compared to pre-COVID level, if started at the beginning and maintained for the entire duration of the second wave and coupled with contact tracing, could suffice to control the epidemic. A very important factor in this result is the presence of contact tracing; without it, the reduction in mobility needs to be substantially larger. The flexibility of our proposed model allows similar analyses to be conducted for other regions even with slightly different data sources for the progression of the epidemic; the extension to more than two waves is straightforward. The model could help policymakers worldwide to make better decisions in terms of the timing and severity of the adopted NPIs.

Nutritional Status and Health-Related Quality of Life in Men with Advanced Castrate-Resistant Prostate Cancer

BACKGROUND

Despite professional recommendations malnutrition is not adequately addressed in cancer patients. Here, we explored whether nutritional status (NS) is associated with HRQoL in men with metastatic castrate-resistant prostate cancer (mCRPC). Methods: Men with mCRPC enrolled into this prospective observational study were allocated to one of the four NS categories based on clinical, laboratory, and patient self-reported criteria: well-nourished (WN), nutritional risk without criteria for cachexia/sarcopenia (NR), sarcopenia, and cachexia. The HRQoL was evaluated by the Functional Assessment of Cancer Therapy-Prostate (FACT-P) questionnaire. Association between NS and self-reported HRQoL was sought by the linear regression model, which was adjusted for known prognostic variables and body mass index. Results: Over the period of two years, 141 patients were enrolled. Their median age was 74.1 years (IQR 68.6-79.4 years) and majority of them were minimally symptomatic. Fifty-nine patients (41.8%) were WN, followed by 24 (17%), 42 (29.8%), and 16 (11.4%) patients with NR, sarcopenia, and cachexia, respectively. As compared to WN patients, all three other NS categories were significant negative predictors of HRQoL (P < 0.04). Conclusions: Abnormal NS is highly prevalent in men with mCRPC and is negatively associated with their HRQoL, which supports the recommendation for management of malnutrition in these patients.

Analysis of time-to-event for observational studies: Guidance to the use of intensity models

This paper provides guidance for researchers with some mathematical background on the conduct of time-to-event analysis in observational studies based on intensity (hazard) models. Discussions of basic concepts like time axis, event definition and censoring are given. Hazard models are introduced, with special emphasis on the Cox proportional hazards regression model. We provide check lists that may be useful both when fitting the model and assessing its goodness of fit and when interpreting the results. Special attention is paid to how to avoid problems with immortal time bias by introducing time-dependent covariates. We discuss prediction based on hazard models and difficulties when attempting to draw proper causal conclusions from such models. Finally, we present a series of examples where the methods and check lists are exemplified. Computational details and implementation using the freely available R software are documented in Supplementary Material. The paper was prepared as part of the STRATOS initiative.

Impact of delays in radiotherapy of head and neck cancer on outcome

BACKGROUND

In head and neck cancer (HNC), the relationship between a delay in starting radiotherapy (RT) and the outcome is unclear. The aim of the present study was to determine the impact of the amount of time before treatment intervention (TTI) and the growth kinetics of individual tumors on treatment outcomes and survival.

METHODS

Two hundred sixty-two HNC patients with 273 primary tumors, treated with definitive (chemo) RT, were retrospectively analyzed. The TTI was defined as the time interval between the date of histopathologic diagnosis and the first day of the RT course. Volumetric data on 57 tumors were obtained from diagnostic and RT planning computer tomography (CT) scans in order to calculate the tumor growth kinetic parameters.

RESULTS

No significant association between locoregional control or cause-specific hazards and TTI was found. The log hazard for locoregional recurrence linearly increased during the first 40 days of waiting for RT, although this was not significant. The median tumor volume relative increase rate and tumor volume doubling time was 3.2%/day and 19 days, respectively, and neither had any impact on locoregional control or cause-specific hazards.

CONCLUSION

The association between a delay in starting RT and the outcome is complex and does not harm all patients waiting for RT. Further research into imaging-derived kinetic data on individual tumors is warranted in order to identify patients at an increased risk of adverse outcomes due to a delay in starting RT.

Course and Outcome of Erythema Migrans in Pregnant Women

Information on Lyme borreliosis (LB) during pregnancy is limited. In the present study, the course and outcome of erythema migrans (EM) in 304 pregnant women, diagnosed in the period 1990–2015, was assessed and compared with that in age-matched non-pregnant women. The frequency of unfavorable outcome of pregnancies was also evaluated. The pregnant women reported constitutional symptoms less frequently than the non-pregnant women (22.4% vs. 37.2%, p < 0.001). Pregnant women diagnosed with EM later during pregnancy had a lower probability of reporting constitutional symptoms (odds ratio = 0.97 for 1-week difference in gestation week at diagnosis of EM, 95% CI: 0.94–0.99, p = 0.02). The outcome of pregnancy was unfavorable in 42/304 (13.8%) patients: preterm birth in 22/42 (52.4%), fetal/perinatal death in 10/42 (23.8%), and/or anomalies in 15/42 (35.7%). Several patients had potential explanation(s) for the unfavorable outcome. In conclusion, the course of early LB during pregnancy is milder than in age-matched non-pregnant women. The outcome of pregnancy with the treatment approach used in the present study (i.v. ceftriaxone 2 g once daily for 14 days) is favorable.

Improvements in the multidisciplinary care are beneficial for survival in amyotrophic lateral sclerosis (ALS): experience from a tertiary ALS center

Objective: The Ljubljana ALS Centre, established in 2002, is the only tertiary center for amyotrophic lateral sclerosis (ALS) in Slovenia. The aim of our study was to evaluate the impact of therapeutic interventions and improvements in the multidisciplinary care on the survival of our patients.Methods: All patients diagnosed with ALS at our center during years 2003-2005 (early group) and 2011-2012 (late group) were included in this retrospective cohort study (n = 124). Kaplan-Meier survival analysis and multiple regression analysis with Cox proportional hazards model were performed to compare survival and to evaluate the differences between the two cohorts.Results: Median survival from the time of diagnosis was 13.0 (95% CI 10.2-15.8) months in the early group and 21.8 (95% CI 17.2-26.4) months in the late group (p = 0.005). In the Cox proportional hazards analysis, the late group of patients was associated with better survival independently of all other prognostic factors (hazard ratio (HR)=0.51, 95% CI = 0.32-0.81, p = 0.004). Survival was also associated with patients' age, use of noninvasive ventilation (NIV) and gastrostomy. The model fit significantly improved when the interaction between the NIV use and the observed time period was added to the model (HR = 0.34, 95% CI = 0.12-0.96, p = 0.041).Conclusions: Our findings suggest that improvements in the multidisciplinary care were beneficial for survival of our patients with ALS. The survival benefit in the late group of our patients could be partially explained by the improvements in the NIV use at our center.

Using pseudo-observations for estimation in relative survival

A common goal in the analysis of the long-term survival related to a specific disease is to estimate a measure that is comparable between populations with different general population mortality. When cause of death is unavailable or unreliable, as for example in cancer registry studies, relative survival methodology is used-in addition to the mortality data of the patients, we use the data on the mortality of the general population. In this article, we focus on the marginal relative survival measure that summarizes the information about the disease-specific hazard. Under additional assumptions about latent times to death of each cause, this measure equals net survival. We propose a new approach to estimation based on pseudo-observations and derive two estimators of its variance. The properties of the new approach are assessed both theoretically and with simulations, showing practically no bias and a close to nominal coverage of the confidence intervals with the precise formula for the variance. The approximate formula for the variance has sufficiently good performance in large samples where the precise formula calculation becomes computationally intensive. Using bladder cancer data and simulations, we show that the behavior of the new approach is very close to that of the Pohar Perme estimator but has the important advantage of a simpler formula that does not require numerical integration and therefore lends itself more naturally to further extensions.

Association between nutritional status (NS) and health-related quality of life (HRQoL) in men with early metastatic castrate-resistant prostate cancer (mCRPC)

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Background: HRQoL is of paramount importance in men with mCRPC. It is not known how NS affects HRQoL in this population of patients. We hypothesized that NS is associated with HRQoL in men with early mCRPC and that NS outperforms body mass index (BMI) in this association. Methods: We prospectively enrolled men with early mCRPC into this study. Patients were assessed, and on the basis of established criteria, four NS categories were defined: normal NS (nNS), nutritional risk without cachexia/sarcopenia (NR), sarcopenia (S) (handgrip strength < 30 kg) and cachexia (C) (Evans`s criteria). HRQoL was assessed by the validated questionnaire Functional Assessment of Cancer Treatment (FACT-P); higher score reflects better HRQoL. After checking for normal distribution, we performed a linear regression model for HRQoL with NS as a dummy variable (with nNS as the reference group). Age, duration of previous androgen deprivation therapy (ADT), hemoglobin level (Hb), prostate-specific antigen (PSA) and BMI were included as covariates into the multivariate model. Results: One hundred forty-one patients were enrolled in our study. At presentation, their mean age was 74.2 years (SD 7.1), and 18 (12.4 %) had visceral metastases. Fifty-eight (41.3%) had nNS, 43 (30.8 %) had sarcopenia, 24 (16.8 %) NR and 16 (11.2 %) C. Mean FACT-P score [SD] in nNS was 115.3 points [22.2], following by 97 [24.6], 98.3 [22.4] and 78.8 [25] points in NR, S and C groups, respectively. We found a significant and consistent association between better NS and worse HRQoL (β [NR:nNS] = -18.2 points; β [S:nNS] = -17 points; β [C:nNS] = -36.5 points; p < 0.001; R² = 0.2). The association remained significant after adjustments (R² = 0.27). Conclusions: Suboptimal NS but not BMI is significantly associated with worse HRQoL in men with early mCRPC. Interventional trials focused on the optimization of NS in men with mCRPC are warranted.[Table: see text]

Diabetes and smoking are more important for prognosis of patients with peripheral arterial disease than some genetic polymorphisms

Background: The role of genetic polymorphisms in peripheral arterial disease (PAD) is incompletely understood. We tested whether selected single nucleotide polymorphisms (SNPs) were associated with PAD and with adverse events in an observational study cohort. Also, the role of diabetes and smoking was studied. Patients and methods: 742 patients with PAD and 713 age- and gender-matched control subjects were subjected to yearly physical and laboratory investigations and were managed for 5 years according to the European guidelines on cardiovascular disease prevention. The occurrence of all-cause death, cardiovascular death, non-fatal myocardial infarction, ischemic stroke or critical limb ischemia (major events) and revascularization procedures (minor events) was recorded. In 655 patients with PAD and 612 control subjects the following SNPs were determined: rs1466408, rs13428968 and rs12803 of NR4A2 gene, rs10499563 of IL6 gene, rs668 and rs12953 of PECAM1 gene, and rs10861032 of Chr12 locus. Results: The distribution of selected SNPs did not differ between patients with PAD and control subjects, and neither between subjects with or without major adverse events. In contrast, diabetes and smoking affected survival and event-free survival. Among patients with PAD, diabetes doubled the hazard ratio (HR) for cardiovascular death and smoking doubled the HR for death or major event. The 5-year survival of diabetics with PAD was 0.80 (CI 0.75-0.85) and of non-diabetics with PAD 0.87 (CI 0.84-0.90), p = 0.045. The 5-year survival of active smokers with PA D was 0.80 (CI 0.75-0.62), of former smokers 0.83 (CI 0.79-0.88), and of never-smokers 0.89 (CI 0.86-0.93), p = 0.024. Conclusions: SNPs of NR4A2, IL6, PECAM1 and Chr12 were not associated with PAD or with major adverse events. However, diabetes and smoking were associated with worse survival and event-free survival in patients with PAD.

Confidence intervals for the Mann–Whitney test

The Mann–Whitney test is a commonly used non-parametric alternative of the two-sample t-test. Despite its frequent use, it is only rarely accompanied with confidence intervals of an effect size. If reported, the effect size is usually measured with the difference of medians or the shift of the two distribution locations. Neither of these two measures directly coincides with the test statistic of the Mann–Whitney test, so the interpretation of the test results and the confidence intervals may be importantly different. In this paper, we focus on the probability that random variable X is lower than random variable Y. This measure is often referred to as the degree of overlap or the probabilistic index; it is in one-to-one relationship with the Mann–Whitney test statistic. The measure equals the area under the ROC curve. Several methods have been proposed for the construction of the confidence interval for this measure, and we review the most promising ones and explain their ideas. We study the properties of different variance estimators and small sample problems of confidence intervals construction. We identify scenarios in which the existing approaches yield inadequate coverage probabilities. We conclude that the DeLong variance estimator is a reliable option regardless of the scenario, but confidence intervals should be constructed using the logit scale to avoid values above 1 or below 0 and the poor coverage probability that follows. A correction is needed for the case when all values from one sample are smaller than the values of the other. We propose a method that improves the coverage probability also in these cases.

Explained variation of excess hazard models

The availability of longstanding collection of detailed cancer patient information makes multivariable modelling of cancer-specific hazard of death appealing. We propose to report variation in survival explained by each variable that constitutes these models. We adapted the ranks explained (RE) measure to the relative survival data setting, ie, when competing risks of death are accounted for through life tables from the general population. RE is calculated at each event time. We introduce weights for each death reflecting its probability to be a cancer death. RE varies between -1 and +1 and can be reported at given times in the follow-up and as a time-varying measure from diagnosis onward. We present an application for patients diagnosed with colon or lung cancer in England. The RE measure shows reasonable properties and is comparable in both relative and cause-specific settings. One year after diagnosis, RE for the most complex excess hazard models reaches 0.56, 95% CI: 0.54 to 0.58 (0.58 95% CI: 0.56-0.60) and 0.69, 95% CI: 0.68 to 0.70 (0.67, 95% CI: 0.66-0.69) for lung and colon cancer men (women), respectively. Stage at diagnosis accounts for 12.4% (10.8%) of the overall variation in survival among lung cancer patients whereas it carries 61.8% (53.5%) of the survival variation in colon cancer patients. Variables other than performance status for lung cancer (10%) contribute very little to the overall explained variation. The proportion of the variation in survival explained by key prognostic factors is a crucial information toward understanding the mechanisms underpinning cancer survival. The time-varying RE provides insights into patterns of influence for strong predictors.

Comparison of the algorithms classifying the ABC and GCB subtypes in diffuse large B-cell lymphoma

Different immunohistochemical algorithms for the classification of the activated B-cell (ABC) and germinal center B-cell (GCB) subtypes of diffuse large B-cell lymphoma (DLBCL) are applied in different laboratories. In the present study, 127 patients with DLCBL were investigated, all treated with rituximab and cyclophosphamide, hydroxydaunorubicin, oncovin and prednisone (CHOP) or CHOP-like regimens between April 2004 and December 2010. Multi-tumor tissue microarrays were prepared and were tested according to 4 algorithms: Hans; modified Hans; Choi; and modified Choi. For 39 patients, the flow cytometric quantification of CD19 and CD20 antigen expression was performed and the level of expression presented as molecules of equivalent soluble fluorochrome units. The Choi algorithm was demonstrated to be prognostic for OS and classified patients into the GCB subgroup with an HR of 0.91. No difference in the expression of the CD19 antigen between the ABC and GCB groups was observed, but the ABC subtype exhibited a decreased expression of the CD20 antigen compared with the GCB subtype.

Selection of Non-small Cell Lung Cancer Patients for Intercalated Chemotherapy and Tyrosine Kinase Inhibitors

BACKGROUND

When treating patients with advanced non-small cell lung cancer (NSCLC) with tyrosine kinase inhibitors and chemotherapy, intercalated schedule with time separation between the two classes of drugs should avoid their mutual antagonism. In a survey of published trials, we focus on relation between eligibility criteria and effectiveness of intercalated treatment.

METHODS

Published documents were identified using major medical databases, conference proceedings and references of published trials. Median progression-free survival (PFS) was taken as the basic parameter of treatment efficacy. Correlation between characteristics of patients and median PFS was assessed through the Pearson's correlation coefficient and the coefficient of determination, separately for first-line and second-line setting.

RESULTS

The series includes 11 single-arm trials and 18 randomized phase II or phase III trials with a total of 2903 patients. Treatment-naive patients or those in progression after first-line treatment were included in 16 and 13 trials, respectively. In 14 trials, only patients with non-squamous histology were eligible. Proportion of patients with non-squamous carcinoma (in first-line setting), proportion of never-smokers (both in first- and second-line setting) and proportion of epidermal growth factor receptor (EGFR) mutant patients (both in first- and second-line setting) showed a moderate or strong correlation with median PFS. In six trials of intercalated treatment applied to treatment-naive EGFR-mutant patients, objective response was confirmed in 83.1% of cases and median PFS was 18.6 months.

CONCLUSIONS

Most suitable candidates for intercalated treatment are treatment-naive patients with EGFR-mutant tumors, as determined from biopsy or liquid biopsy. For these patients, experience with intercalated treatment is most promising and randomized trials with comparison to the best standard treatment are warranted.

DNA Methylation and Hydroxymethylation Profile of CD34+-Enriched Cell Products Intended for Autologous CD34+ Cell Transplantation

Epigenetic dysregulation has been shown to limit functional capacity of aging hematopoietic stem cells, which may contribute to impaired outcome of hematopoietic stem cell-based therapies. The aim of our study was to gain better insight into the epigenetic profile of CD34⁺-enriched cell products intended for autologous CD34⁺ cell transplantation in patients with cardiomyopathy. We found global DNA methylation content significantly higher in immunoselected CD34⁺ cells compared to leukocytes in leukapheresis products (2.33 ± 1.03% vs. 1.84 ± 0.86%, p = 0.04). Global DNA hydroxymethylation content did not differ between CD34⁺ cells and leukocytes (p = 0.30). By measuring methylation levels of 94 stem cell transcription factors on a ready-to-use array, we identified 15 factors in which average promoter methylation was significantly different between leukocytes and CD34⁺ cells. The difference was highest for HOXC12 (58.18 ± 6.47% vs. 13.34 ± 24.18%, p = 0.0009) and NR2F2 (51.65 ± 25.89% vs. 7.66 ± 21.43%, p = 0.0045) genes. Our findings suggest that global DNA methylation and hydroxymethylation patterns as well as target methylation profile of selected genes in CD34⁺-enriched cell products do not differ significantly compared to leukapheresis products and, thus, can tell us little about the functional capacity and regenerative properties of CD34⁺ cells. Future studies should examine other CD34⁺ cell graft characteristics, which may serve as prognostic tools for autologous CD34⁺ cell transplantation.

On comparison of net survival curves

Background

Relative survival analysis is a subfield of survival analysis where competing risks data are observed, but the causes of death are unknown. A first step in the analysis of such data is usually the estimation of a net survival curve, possibly followed by regression modelling. Recently, a log-rank type test for comparison of net survival curves has been introduced and the goal of this paper is to explore its properties and put this methodological advance into the context of the field.

Methods

We build on the association between the log-rank test and the univariate or stratified Cox model and show the analogy in the relative survival setting. We study the properties of the methods using both the theoretical arguments as well as simulations. We provide an R function to enable practical usage of the log-rank type test.

Results

Both the log-rank type test and its model alternatives perform satisfactory under the null, even if the correlation between their p-values is rather low, implying that both approaches cannot be used simultaneously. The stratified version has a higher power in case of non-homogeneous hazards, but also carries a different interpretation.

Conclusions

The log-rank type test and its stratified version can be interpreted in the same way as the results of an analogous semi-parametric additive regression model despite the fact that no direct theoretical link can be established between the test statistics.

Electronic supplementary material

The online version of this article (doi:10.1186/s12874-017-0351-3) contains supplementary material, which is available to authorized users.

Analysing population-based cancer survival - settling the controversies

BACKGROUND

The relative survival field has seen a lot of development in the last decade, resulting in many different and even opposing suggestions on how to approach the analysis.

METHODS

We carefully define and explain the differences between the various measures of survival (overall survival, crude mortality, net survival and relative survival ratio) and study their differences using colon and prostate cancer data extracted from the national population-based cancer registry of Slovenia as well as simulated data.

RESULTS

The colon and prostate cancer data demonstrate clearly that when analysing population-based data, it is useful to split the overall mortality in crude probabilities of dying from cancer and from other causes. Complemented by net survival, it provides a complete picture of cancer survival in a given population. But when comparisons of different populations as defined for example by place or time are of interest, our simulated data demonstrate that net survival is the only measure to be used.

CONCLUSIONS

The choice of the method should be done in two steps: first, one should determine the measure of interest and second, one should choose among the methods that estimate that measure consistently.

Long-term outcomes of high dose treatment and autologous stem cell transplantation in follicular and mantle cell lymphomas - a single centre experience

BACKGROUND

Advanced follicular lymphoma (FL) and mantle cell lymphoma (MCL) are incurable diseases with conventional treatment. The high dose treatment (HDT) with autologous stem cell transplantation (ASCT), however, offers a certain proportion of these patients the prospect of a prolonged disease-free and overall survival. The aim of this study was to investigate the event free survival (EFS) and overall survival (OS) in patients with FL and MCL treated with ASCT.

PATIENTS AND METHODS

Seventeen patients with FL and 29 patients with MCL were included, 15 of them were transplanted to consolidate the response to second line treatment and 24 to consolidate their first remission, respectively. All were conditioned with total body irradiation (TBI) and high dose cyclophosphamide between 2006 and 2014 and all were transplanted with peripheral blood stem cells.

RESULTS

The estimated 5-year OS for FL was 87.8% (95% confidence interval [CI] 59.5%-96.8%) and for MCL 79.3% (95% CI 56.1%-91.1%), respectively. The estimated 5-year EFS for FL was 76.0% (95% CI 48.0%-90.3%) and for MCL 69.8% (95% CI 45.5%-84.8%), respectively. There were no secondary hematological malignancies observed in either group.

CONCLUSIONS

Based on above results, the ASCT with TBI is a good treatment option in terms of long-term survival for patients with follicular and mantle cell lymphoma demonstrating a relatively low rate of late toxicities and secondary malignancies.

Survival and event-free survival of patients with peripheral arterial disease undergoing prevention of cardiovascular disease

BACKGROUND

Patients with peripheral arterial disease (PAD) are at very high risk for cardiovascular events. How do patients with PAD differ from age- and sex-matched controls in survival, major ischemic events and revascularization procedures when both groups were managed according to the European guidelines on cardiovascular disease prevention?

METHODS

Patients with PAD (N.=742) and 713 age and sex-matched control subjects without PAD, both groups aged 65±9 years at inclusion, were managed for 5 years according to the European guidelines on cardiovascular disease prevention and evaluated yearly for occurrence of death, non-fatal major ischemic events and revascularization procedures (minor events).

RESULTS

In the PAD group, the 5-year survival was 84.7% (CI 82.1-87.3%) vs. 93.3% (CI 91.5-95.2%) in the control group, P<0.001. In the PAD group the proportion of cardiovascular deaths did not differ significantly from non-cardiovascular deaths (6.9 vs. 8.4%, P=0.14), while in the control group cardiovascular deaths were less frequent (2.4 vs. 4.3%, P=0.05). The groups differed in 5-year major event-free survival: 76.7% (CI 73.7-79.8%) in PAD vs. 89.9% (CI 87.7 -92.2%) in controls, P<0.001, and in event-free survival: 56.2% (CI 52.7-59.9%) in PAD vs. 82.4% (CI 79.9-85.3%) in controls, P<0.001.

CONCLUSIONS

Patients with PAD had a higher risk of all-cause death, major and minor non-fatal cardiovascular events compared to control subjects. In our group, cardiovascular events were not the leading cause of death in patients with PAD (ClinicalTrials.gov number NCT00761969.).

Risk of Thromboembolic Events in Patients with Non-Valvular Atrial Fibrillation After Dabigatran or Rivaroxaban Discontinuation - Data from the Ljubljana Registry

Background and Aim

Interruption of anticoagulant treatment with warfarin or non-vitamin K antagonist oral anticoagulants (NOAC) represents a vulnerable period with an increased risk of thromboembolic events. What is the incidence of thromboembolic events in real-life patients with non-valvular atrial fibrillation treated with NOAC who had a discontinuation or cessation of treatment in comparison to patients on continuous treatment?

Patients and Methods

Registry data from 866 patients with non-valvular atrial fibrillation, aged 74.3 (SD 9.8) years, with an average CHADS₂ score of 2.1 (SD 1.2), who were started on dabigatran or rivaroxaban, were analysed for thromboembolic events and survival. Patients who had temporary or permanent discontinuation of NOAC were compared to patients on continuous NOAC treatment.

Results

Among 866 patients started on NOAC, 705 were treated without interruption, 84 patients had temporary interruption (69 because of planned invasive procedures, 10 due to bleeding, 5 for other causes) and 77 had permanent cessation of NOAC treatment. In patients without interruptions, the incidence of thromboembolic events was 1.0 (95% CI 0.4–2.1) per 100 patient-years, while in patients with interruption/cessation the rate of thromboembolic events was 21.6 (95% CI 10.3–45.2) per 100 patient-years, p < 0.001. There was a distinct clustering of thromboembolic events in the first weeks of NOAC discontinuation with the median occurring on day 14 (range 1–37 days) after discontinuation.

Conclusion

Dabigatran and rivaroxaban offered good protection against thromboembolic events during treatment, but interruption of NOAC treatment increased the short-term thromboembolic risk more than 20-fold.

Analyzing disease recurrence with missing at risk information

When analyzing time to disease recurrence, we sometimes need to work with data where all the recurrences are recorded, but no information is available on the possible deaths. This may occur when studying diseases of benign nature where patients are only seen at disease recurrences or in poorly-designed registries of benign diseases or medical device implantations without sufficient patient identifiers to obtain their dead/alive status at a later date. When the average time to disease recurrence is long enough in comparison with the expected survival of the patients, statistical analysis of such data can be significantly biased. Under the assumption that the expected survival of an individual is not influenced by the disease itself, general population mortality tables may be used to remove this bias. We show why the intuitive solution of simply imputing the patient's expected survival time does not give unbiased estimates of the usual quantities of interest in survival analysis and further explain that cumulative incidence function analysis does not require additional assumptions on general population mortality. We provide an alternative framework that allows unbiased estimation and introduce two new approaches: an iterative imputation method and a mortality adjusted at risk function. Their properties are carefully studied, with the results supported by simulations and illustrated on a real-world example.

Inter-rater reliability of the GNRB® knee arthrometer

BACKGROUND

In clinical settings, where arthrometers are mainly used by different clinicians, knowing the inter-rater reliability of the instrument is crucial in order for the results from different examiners to be accurately interpreted and limitations fully understood. The aim of this study was to evaluate the inter-rater reliability of the GNRB® knee arthrometer.

METHODS

Knee anterior laxity in both knees was tested in a group of young, uninjured subjects (N=27, 13 females) by two examiners. Knee anterior laxity was calculated at test forces of 134 N and 250 N with values presented for the unstandardised and standardised conditions (relative to patellar stabilisation force).

RESULTS

The ICCs ranged from 0.220 to 0.424.

CONCLUSIONS

The inter-rater reliability of the GNRB® knee arthrometer is low.

Direct microscopic monitoring of initial and dynamic clot lysis using plasmin or rt-PA in an in vitro flow system

INTRODUCTION

Plasmin is a direct-acting thrombolytic agent with a favorable safety profile upon intra-arterial delivery in pre-clinical and phase I studies. However, the thrombolytic efficacy of plasmin, relative to that of rt-PA, remains to be established. We have compared the dynamics of clot lysis with plasmin or rt-PA in an in vitro perfusion system, in which thrombolytic agent is administered locally, allowed to induce lysis for short intervals, then washed with plasma in a re-circulation circuit.

MATERIALS AND METHODS

Whole blood human clots were prepared in observation chambers, exposed to plasmin or rt-PA at equimolar concentrations (1.2/1.0, 1.8/1.5 and 2.4/2.0 mg/ml) for measured intervals of time, followed by perfusion with human plasma. Clot size was monitored by digital analysis of sequential photographs obtained through an optical microscope.

RESULTS

Plasma perfusion after incubation with thrombolytic agent rapidly removed superficial clot fragments. This initial decrease in clot size was greater with plasmin than with rt-PA when tested at the highest concentrations of agent (0.63 ± 0.11 vs. 0.30 ± 0.11, p=0.001 for clots with non-cross-linked fibrin and 0.53 ± 0.15 vs. 0.14 ± 0.15, p=0.02, for clots with cross-linked-fibrin). Subsequent clot lysis during plasma flow was greater after prior incubation with rt-PA. Longer incubation times of plasmin resulted in larger portions of the clot being washed free. Repeated plasmin incubations and plasma perfusions of a clot successfully induced stepwise reductions in clot size.

CONCLUSIONS

Initial clot lysis is greater with direct exposure using plasmin than rt-PA. During washout and circulation with plasma, rt-PA induced continued clot lysis, while plasmin lysis was curtailed, presumably because of plasmin inhibition.

Outcomes of peritoneal dialysis patients and switching to hemodialysis: a competing risks analysis

BACKGROUND

We performed a review of a large incident peritoneal dialysis cohort to establish the impact of current practice and that of switching to hemodialysis.

METHODS

Patients starting peritoneal dialysis between 2004 and 2010 were included and clinical data at start of dialysis recorded. Competing risk analysis and Cox proportional hazards model with time-varying covariate (technique failure) were used.

RESULTS

Of 286 patients (median age 57 years) followed for a median of 24.2 months, 76 were transplanted and 102 died. Outcome probabilities at 3 and 5 years respectively were 0.69 and 0.53 for patient survival (or transplantation) and 0.33 and 0.42 for technique failure. Peritonitis caused technique failure in 42%, but ultrafiltration failure accounted only for 6.3%. Davies comorbidity grade, creatinine and obesity (but not residual renal function or age) predicted technique failure. Due to peritonitis deaths, technique failure was an independent predictor of death hazard. When successful switch to hemodialysis (surviving more than 60 days after technique failure) and its timing were analyzed, no adverse impact on survival in adjusted analysis was found. However, hemodialysis via central venous line was associated with an elevated death hazard as compared to staying on peritoneal dialysis, or hemodialysis through a fistula (adjusted analysis hazard ratio 1.97 (1.02 - 3.80)).

CONCLUSIONS

Once the patients survive the first 60 days after technique failure, the switch to hemodialysis does not adversely affect patient outcomes. The nature of vascular access has a significant impact on outcome after peritoneal dialysis failure.

Robotic knee laxity testing: reliability and normative data

PURPOSE

To evaluate the reliability of the GeNouRoB knee arthrometer and present normative values of knee anterior laxity using this device on young females.

METHODS

Anterior laxity in both knees was tested in two groups of young, uninjured females using the hamstrings electromyography biofeedback feature of the device. There were 13 participants in the group tested for reliability and 23 for the normative study. Laxity (mm of movement of the proximal tibia in the anterior direction relative to the femur) was calculated at test forces of 134 N and 250 N with values presented for the unstandardised and standardised (relative to stabilisation force) conditions.

RESULTS

The relative reliability (95% limits of agreement) of the device for laxity at a test force of 134 N was 2 to 3mm. Left knee anterior laxity was almost 1mm greater than the right.

CONCLUSIONS

The relative reliability of the GeNouRoB arthrometer is comparable to the KT device. In agreement with previous work on the nonrobotic KT arthrometer, the knee anterior laxity values found with the GeNouRoB are greater in the left as compared to the right knee.

Has equity in relative survival improved over time in Finland - a methodological exercise

BACKGROUND

Population-based relative survival is widely used as a method of monitoring the success of cancer control. This success may not be relevant only for an entire country but also regional developments over time are of interest. It would not only be important that the relative survival improved but also that the differences between regions decreased over time.

METHODS

In this paper the authors show how relative survival methods can be used to study such differences. In addition to standard methods, some more recently introduced approaches are used, most notably a method for checking the goodness of fit of the relative survival model. This gives confidence in the obtained results and provides additional insight when assumptions are not met.

RESULTS

An analysis of cancers of the colon and ovary by cancer control region in Finland in 1953-2003 shows an overall improvement in relative survival, accompanied in colon cancer also by a decrease of differences in relative survival between the regions. Thus, the desired course was observed in colon cancer but not in cancer of the ovary.

CONCLUSIONS

These results, applied to further sites, should lead to investigation of differences in cancer control policies between regions.

Rate and risk of anterior cruciate ligament injury among sportswomen in Slovenia

CONTEXT

Anterior cruciate ligament (ACL)-injury rate is greater among female athletes than among male athletes.

OBJECTIVE

To investigate the rate and risk of ACL injury among Slovenian sportswomen playing professional basketball, team handball, or volleyball.

DESIGN

Prospective cohort study.

SETTING

The Slovenian National Organizations of basketball, team handball, and volleyball.

PATIENTS OR OTHER PARTICIPANTS

During the 2003-2004 season, we prospectively followed 585 Slovenian sportswomen registered in the Slovenian National Organizations of basketball, team handball, and volleyball.

MAIN OUTCOME MEASURE(S)

We asked sportswomen and coaches to document the occurrence of every significant traumatic knee injury requiring medical attention. Injury rate and injury risk were calculated for sportswomen in each sport group. To calculate injury rate, we estimated the average exposure of each sportswoman during the research period.

RESULTS

During the 2003-2004 season, 585 Slovenian sportswomen sustained 12 ACL injuries. The ACL-injury risk was different in athletes participating in the various sports, with basketball players having the greatest ACL-injury risk and volleyball players having the lowest ACL-injury risk (P  =  .04). The risk of ACL injury among Slovenian sportswomen was 2.1 per 100 athletes (95% confidence interval  =  0.9, 3.2), whereas the rate of ACL injury was 0.037 per 1000 exposure hours (95% confidence interval  =  0.016, 0.06).

CONCLUSIONS

Overall differences in injury risk were found among sports, but no differences were noted among divisions within sports. No differences for injury rate were observed between or within sports. The rate and risk of ACL injury among Slovenian sportswomen are high, with basketball players having the greatest ACL-injury risk.

Correlates of knee anterior laxity in sportswomen

The purpose of this study was to evaluate whether any of the following factors are related to knee anterior laxity in healthy sportswomen: anthropometric characteristics, lower limb alignment characteristics, hormone-related factors and sport history. Six hundred and sixteen sportswomen were tested in the pre-season. The data have been analysed using linear regression for possible association of knee anterior laxity with other variables. Univariate linear regression indicated a positive association of knee anterior laxity with knee extension and navicular drop and a negative association with body height. Multivariate linear regression analysis showed statistically significant associations between knee anterior laxity and the combination of passive knee extension and the chosen sport (R(2)=0.089; p<0.05). The combination of passive knee extension and sport type was found to be related to the amount of knee anterior laxity, although the association was weak with this combination of factors able to explain only about 9% of the variability in laxity. Knowing which factors influence the amount of knee anterior laxity will help us to better interpret the results of knee anterior laxity testing and help us to understand the possible role of knee anterior laxity as a risk factor for knee injury.

Pseudo-observations in survival analysis

We review recent work on the application of pseudo-observations in survival and event history analysis. This includes regression models for parameters like the survival function in a single point, the restricted mean survival time and transition or state occupation probabilities in multi-state models, e.g. the competing risks cumulative incidence function. Graphical and numerical methods for assessing goodness-of-fit for hazard regression models and for the Fine—Gray model in competing risks studies based on pseudo-observations are also reviewed. Sensitivity to covariate-dependent censoring is studied. The methods are illustrated using a data set from bone marrow transplantation.

Trends in survival after childhood cancer in Slovenia between 1957 and 2007

OBJECTIVES

To evaluate childhood cancer survival in Slovenia, to provide results comparable to ACCIS studies, and to study the effect of recorded variables on 5-year survival.

METHODS

The data are registry-based and present a unique collection in terms of control and homogeneity. Survival was explored using Kaplan-Meier estimates and the Cox model. Restricted cubic splines were used to illustrate the nonlinearity of the age and year of diagnosis effect for the four chosen diagnoses.

RESULTS

The data set includes 1827 children examined from 1957 to 2002 with the follow-up ending 2007. The overall 5-year survival increased from 0.26 (95%CI [0.21, 0.33]) before 1973 to 0.8 (95% CI [0.74, 0.85]) for patients diagnosed in the period 1998-2002. It is best for Hodgkin disease and leukemia; for non-Hodgkin lymphoma (NHL) and intracranial and intraspinal neoplasms (CNS) the rate of improvement has been slowing down since 1990. Survival is significantly associated with age at diagnosis for patients with leukemia, CNS, NHL, and neuroblastoma (p < .001), the association varies between diseases. Hazard decreases with age for children with CNS and NHL, increases for children with neuroblastoma, and is quadratic with its lowest point at the age of about 5 years for children with leukemia.

CONCLUSIONS

The survival experience in Slovenia compares well with those of large samples in the United States SEER program 1975-1995 and the data collected by ACCIS from 62 population-based cancer registries in Europe. The hazard of dying has been decreasing constantly, mainly due to improvements in leukemia treatment.

Checking hazard regression models using pseudo-observations

Graphical methods for model diagnostics are an essential part of the model fitting procedure. However, in survival analysis, the plotting is always hampered by the presence of censoring. Although model specific solutions do exist and are commonly used, we present a more general approach that covers all the models using the same framework. The pseudo-observations enable us to calculate residuals for each individual at each time point regardless of censoring and provide methods for simultaneously checking all the assumptions of both the Cox and the additive model. We introduce methods for single as well as multiple covariate cases and complement them with corresponding goodness-of-fit tests. The methods are illustrated on simulated as well as real data examples.

Insulin Gene Polymorphism in Women with Polycystic Ovary Syndrome

Insulin resistance is one of the main characteristics of polycystic ovary syndrome (PCOS) and is probably genetically predisposed. Possible associations of variable nucleotide tandem repeat (VNTR) polymorphism of the insulin gene ( INS) with insulin resistance and PCOS in Slovene patients were investigated. A total of 117 PCOS patients and 108 age-matched female controls were genotyped for the INS VNTR polymorphism using real-time polymerase chain reaction and measurement of appropriate biochemical and clinical parameters. Serum fasting insulin ( I0) levels and the homeostasis model assessment index were significantly elevated in PCOS patients compared with controls. Class III INS VNTR alleles were significantly more frequent in the PCOS group. The interaction between body mass index and INS VNTR genotype was a significant predictor of serum I0 level. The interaction of obesity and the III/III INS VNTR genotype might be a risk factor for the development of PCOS.

Inference for outcome probabilities in multi-state models

In bone marrow transplantation studies, patients are followed over time and a number of events may be observed. These include both ultimate events like death and relapse and transient events like graft versus host disease and graft recovery. Such studies, therefore, lend themselves for using an analytic approach based on multi-state models. We will give a review of such methods with emphasis on regression models for both transition intensities and transition- and state occupation probabilities. Both semi-parametric models, like the Cox regression model, and parametric models based on piecewise constant intensities will be discussed.

An approach to estimation in relative survival regression

The goal of relative survival methodology is to compare the survival experience of a cohort with that of the background population. Most often an additive excess hazard model is employed, which assumes that each person's hazard is a sum of 2 components--the population hazard obtained from life tables and an excess hazard attributable to the specific condition. Usually covariate effects on the excess hazard are assumed to have a proportional hazards structure with parametrically modelled baseline. In this paper, we introduce a new fitting procedure using the expectation-maximization algorithm, treating the cause of death as missing data. The method requires no assumptions about the baseline excess hazard thus reducing the risk of bias through misspecification. It accommodates the possibility of knowledge of cause of death for some patients, and as a side effect, the method yields an estimate of the ratio between the excess and the population hazard for each subject. More importantly, it estimates the baseline excess hazard flexibly with no additional degrees of freedom spent. Finally, it is a generalization of the Cox model, meaning that all the wealth of options in existing software for the Cox model can be used in relative survival. The method is applied to a data set on survival after myocardial infarction, where it shows how a particular form of the hazard function could be missed using the existing methods.

Androgen receptor gene (CAG)n polymorphism in patients with polycystic ovary syndrome

The aim of the present case-control study was to evaluate the incidence of the (CAG)(n)AR polymorphism in Slovene polycystic ovary syndrome (PCOS) patients. The polymorphism was not found to be a major risk factor for the presence of PCOS and for hyperandrogenemia in PCOS.