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P-values have played a central role in the advancement of research in virtually all scientific fields; however, there has been significant controversy over their use. “The ASA president’s task force statement on statistical significance and replicability” has provided a solid basis for resolving the quarrel, but although the significance part is clearly dealt with, the replicability part raises further discussions. Given the clear statement regarding significance, in this article, we consider the validity of p-value use for statistical inference as de facto. We briefly review the bibliography regarding the relevant controversy in recent years and illustrate how already proposed approaches, or slight adaptations thereof, can be readily implemented to address both significance and reproducibility, adding credibility to empirical study findings. The definitions used for the notions of replicability and reproducibility are also clearly described. We argue that any p-value must be reported along with its corresponding s-value followed by (1−α)% confidence intervals and the rejection replication index.

Research compendium for the manuscript Pesigan, I. J. A., Sun, R. W., & Cheung, S. F. (2023). betaDelta and betaSandwich: Confidence intervals for standardized regression coefficients in R. Multivariate Behavioral Research. https://doi.org/10.1080/00273171.2023.2201277

PURPOSE Overexpression of the HER2 protein occurs in 25% to 30% of human breast cancers and leads to a particularly aggressive form of the disease. Efficacy and safety of recombinant humanized anti-HER2 monoclonal antibody as a single agent was evaluated in women with HER2-overexpressing metastatic breast cancer that had progressed after chemotherapy for metastatic disease. PATIENTS AND METHODS Two hundred twenty-two women, with HER2-overexpressing metastatic breast cancer that had progressed after one or two chemotherapy regimens, were enrolled. Patients received a loading dose of 4 mg/kg intravenously, followed by a 2-mg/kg maintenance dose at weekly intervals. RESULTS Study patients had advanced metastatic disease and had received extensive prior therapy. A blinded, independent response evaluation committee identified eight complete and 26 partial responses, for an objective response rate of 15% in the intent-to-treat population (95% confidence interval, 11% to 21%). The median duration of response was 9.1 months; the median duration of survival was 13 months. The most common adverse events, which occurred in approximately 40% of patients, were infusion-associated fever and/or chills that usually occurred only during the first infusion, and were of mild to moderate severity. These symptoms were treated successfully with acetaminophen and/or diphenhydramine. The most clinically significant adverse event was cardiac dysfunction, which occurred in 4.7% of patients. Only 1% of patients discontinued the study because of treatment-related adverse events. CONCLUSION Recombinant humanized anti-HER2 monoclonal antibody, administered as a single agent, produces durable objective responses and is well tolerated by women with HER2-overexpressing metastatic breast cancer that has progressed after chemotherapy for metastatic disease. Side effects that are commonly observed with chemotherapy, such as alopecia, mucositis, and neutropenia, are rarely seen.

Butler’s TALC (Tourism Area Life Cycle Model) is a descriptive model that has become one of the most influential and widely referenced approaches in the analysis of tourism area development. However, from an empirical point of view, and despite many attempts, the model encounters difficulties when making it operational. This article advocates the use of statistical confidence intervals as a useful tool for determining the various stages through which destinations evolve.

Speech-recognition tests are a routine component of the clinical hearing evaluation. The most common type of test uses recorded monosyllabic words presented in quiet. The interpretation of test scores relies on an understanding of the variance of repeated tests. Confidence intervals are useful for determining if two scores are significantly different or if the difference is due to the variability of test scores. Because the response to each test item is binary, either correct or incorrect, the binomial distribution has been used to estimate confidence intervals. This method requires that test scores be independent. If the scores are not independent, the binomial distribution will not accurately estimate the variance of repeated scores. A previously published dataset with repeated scores from normal-hearing and hearing-impaired listeners was used to derive confidence intervals from actual test scores in contrast to the predicted confidence intervals in earlier reports. This analysis indicates that confidence intervals predicted by the binomial distribution substantially overestimate the variance of repeated scores resulting in erroneously broad confidence intervals. High correlations were found for repeated scores, indicating that scores are not independent. The interdependence of repeated scores invalidates confidence intervals predicted by the binomial distribution. Confidence intervals and confidence levels for repeated measures were determined empirically from measured test scores to assist in interpreting differences between repeat scores.

Background Providing estimates of uncertainty for statistical quantities is important for statistical inference. When the statistical quantity of interest is a survival curve, which is a function over time, the appropriate type of uncertainty estimate is a confidence band constructed to account for the correlation between points on the curve, we will call this a simultaneous confidence band. This, however, is not the type of confidence band provided in standard software, which is constructed by joining the confidence intervals at given time points. Methods We show that this type of band does not have desirable joint/simultaneous coverage properties in comparison to simultaneous bands. Results There are different ways of constructing simultaneous confidence bands, and we find that bands based on the likelihood ratio appear to have the most desirable properties. Although there is no standard software available in the three major statistical packages to compute likelihood-based simultaneous bands, we summarise and give code to use available statistical software to construct other simultaneous forms of bands, which we illustrate using a study of colon cancer. Conclusions There is a need for more user-friendly statistical software to compute simultaneous confidence bands using the available methods.

Based on our national outpatient sentinel surveillance, we have developed a novel approach to determine respiratory syncytial virus (RSV) epidemic seasons in Germany by using RSV positivity rate and its lower limit of 95% confidence interval. This method was evaluated retrospectively on nine RSV seasons, and it is also well-suited to describe off-season circulation of RSV in near real time as observed for seasons 2020/21 and 2021/22 during the COVID-19 pandemic. Prospective application is of crucial importance to enable timely actions for health service delivery and prevention.

Objective: We examined whether individual differences in positive and negative affective states predicted dual-task costs using an established Dual-Task Walking protocol in non-demented older adults. We hypothesized that positive and negative affect would be associated with smaller and larger dual-task costs, respectively. Methods: Participants ( N = 403; mean age = 76.22 ± 6.55; females = 56%) completed the Positive and Negative Affect Schedule and the walking protocol involving three conditions: Single-Task-Alpha, Single-Task-Walk (STW), and Dual-Task-Walk (DTW). Gait velocity was assessed via an instrumented walkway. Results: Negative affect was associated with greater decline in gait velocity from STW to DTW (95% confidence interval [−0.73 to −0.03]) but not the decline of the rate of correct letter generation. There was no significant relationship between positive affect and DTW performance. Discussion: Findings suggest negative affect is adversely associated with allocation of attentional resources, leading to worse mobility outcomes in older adults.

The objective of this study was to explore the predictive value of electrocardiogram (ECG) based on intelligent analysis algorithm for atrial fibrillation (AF) in elderly patients undergoing coronary artery bypass grafting (CABG). Specifically, 106 elderly patients with coronary heart disease who underwent CABG in the hospital were selected, including 52 patients with postoperative AF (AF group) and 54 patients without arrhythmia (control group). Within 1-3 weeks after operation, the dynamic ECG monitoring system based on Gentle AdaBoost algorithm constructed in this study was adopted. After the measurement of the 12-lead P wave duration, the maximum P wave duration (Pmax) and minimum P wave duration (Pmin) were recorded. As for simulation experiments, the same data was used as the back-propagation algorithm. The results showed that for the detection accuracy of the test samples, the Gentle AdaBoost algorithm showed 93.7% accuracy after the first iteration, and the Gentle AdaBoost algorithm was 16.1% higher than the back-propagation algorithm. Compared with the control group, the detection rate of arrhythmia in patients after CABG was significantly lower ( P < 0.05 ). Bivariate logistic regression analysis on Pmax and Pmin showed as follows: Pmax: 95% confidential interval (CI): 1.024-1.081, P < 0.05 ; Pmin: 95% CI: 1.036-1.117, P < 0.05 . The sensitivity of Pmax and Pmin in predicting paroxysmal AF was 78.2% and 73.4%, respectively; the specificity of them was 80.1% and 85.6%, respectively; the positive predictive value was 81.2% and 83.4%, respectively; and the negative predictive value was 79.5% and 75.3%, respectively. In conclusion, the generalization ability of Gentle AdaBoost algorithm was better than that of back-propagation algorithm, and it can identify arrhythmia better. Pmax and Pmin were important indicators of AF after CABG.

Concordance refers to the probability that subjects with high values on one variable also have high values on another variable. This index has wide application in practice, as a measure of effect size in group-comparison studies, an index of accuracy in diagnostic studies, and a discrimination index for prediction models. Herein, we provide a unified framework for statistical inference involving concordance indices for standard variables of binary, ordinal, and continuous types. In particular, we develop confidence interval procedures for a single concordance index and differences between two correlated indices. Simulation results show that procedures based on logit-transformation for a single index and Fisher'smml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"mml:miz/mml:mi/mml:math-transformation for a difference between indices perform very well in terms of coverage and tail errors even when the sample size is as small as 30, unless the concordance is high and the standard is a binary variable for which at least 50 subjects are needed. We illustrate the procedures for a variety of standard variables with previously published data. Illustrative SAS code is provided.

Left-truncated data are constructed from the time of an initial event and the time of the event of interest. That is to say, each individual represented by such data is exposed to an event prior to the event of interest, and both times are recorded. Weighted log-rank testing is commonly used for such data. In this paper, a saddlepoint approximation method is provided for computingip/i-values of the permutation distribution of tests from the weighted log-rank testing in the presence of left-truncated data and Wei's urn design. A simulation study is used to assess the efficiency of the saddlepoint approximation. The accuracy of the saddlepoint approximation in comparison to the normal approximation enables us to compute accurate confidence intervals for the treatment effect.

We consider partially observed binary matched-pair data. We assume that the incomplete subjects are missing at random. Within this missing framework, we propose an EM-algorithm based approach to construct an interval estimator of the proportion difference incorporating all the subjects. In conjunction with our proposed method, we also present two improvements to the interval estimator through some correction factors. The performances of the three competing methods are then evaluated through extensive simulation. Recommendation for the method is given based on the ability to preserve type-I error for various sample sizes. Finally, the methods are illustrated in two real-world data sets. An R-function is developed to implement the three proposed methods.

This prespecified subanalysis of the global, randomized controlled phase III KEYNOTE‐024 study of pembrolizumab vs chemotherapy in previously untreated metastatic non‐small‐cell lung cancer without EGFR/ALK alterations and a programmed death ligand 1 (PD‐L1) tumor proportion score of 50% or higher evaluated clinical outcomes among patients enrolled in Japan. Treatment consisted of pembrolizumab 200 mg every 3 weeks (35 cycles) or platinum‐based chemotherapy (four to six cycles). The primary end‐point was progression‐free survival; secondary end‐points included overall survival and safety. Of 305 patients randomized in KEYNOTE‐024 overall, 40 patients were enrolled in Japan (all received treatment: pembrolizumab, n = 21; chemotherapy, n = 19). Median progression‐free survival was 41.4 (95% confidence interval [CI], 4.2‐42.5) months with pembrolizumab and 4.1 (95% CI, 2.8‐8.3) months with chemotherapy (hazard ratio [HR], 0.27 [95% CI, 0.11‐0.65]; one‐sided, nominal P = .001). Median overall survival was not reached (NR) (95% CI, 22.9‒NR) and 21.5 (95% CI, 5.2‐35.0) months, respectively (HR, 0.39 [95% CI, 0.17‐0.91]; one‐sided, nominal P = .012). Treatment‐related adverse events occurred in 21/21 (100%) pembrolizumab‐treated and 18/19 (95%) chemotherapy‐treated patients; eight patients (38%) and nine patients (47%), respectively, had grade 3‐5 events. Immune‐mediated adverse events and infusion reactions occurred in 11 pembrolizumab‐treated patients (52%) and four chemotherapy‐treated patients (21%), respectively; four patients (19%) and one patient (5%), respectively, had grade 3‐5 events. Consistent with results from KEYNOTE‐024 overall, first‐line pembrolizumab improved progression‐free survival and overall survival vs chemotherapy with manageable safety among Japanese patients with metastatic non‐small‐cell lung cancer without EGFR/ALK alterations and a PD‐L1 tumor proportion score of 50% or higher. The trial is registered with Clinicaltrials.gov: NCT02142738., This prespecified subanalysis of the global, randomized controlled phase III KEYNOTE‐024 study of pembrolizumab vs chemotherapy in previously untreated metastatic non‐small‐cell lung cancer without EGFR/ALK alterations and a PD‐L1 tumor proportion score of 50% or higher evaluated clinical outcomes among patients enrolled in Japan. Consistent with results from KEYNOTE‐024 overall, first‐line pembrolizumab improved progression‐free survival and overall survival vs chemotherapy with manageable safety among 40 Japanese patients in the study.

Stratification is commonly employed in clinical trials to reduce the chance covariate imbalances and increase the precision of the treatment effect estimate. We propose a general framework for constructing the confidence interval (CI) for a difference or ratio effect parameter under stratified sampling by the method of variance estimates recovery (MOVER). We consider the additive variance and additive CI approaches for the difference, in which either the CI for the weighted difference, or the CI for the weighted effect in each group, or the variance for the weighted difference is calculated as the weighted sum of the corresponding stratum-specific statistics. The CI for the ratio is derived by the Fieller and log-ratio methods. The weights can be random quantities under the assumption of a constant effect across strata, but this assumption is not needed for fixed weights. These methods can be easily applied to different endpoints in that they require only the point estimate, CI, and variance estimate for the measure of interest in each group across strata. The methods are illustrated with two real examples. In one example, we derive the MOVER CIs for the risk difference and risk ratio for binary outcomes. In the other example, we compare the restricted mean survival time and milestone survival in stratified analysis of time-to-event outcomes. Simulations show that the proposed MOVER CIs generally outperform the standard large sample CIs, and that the additive CI approach performs slightly better than the additive variance approach., Comment: 13 pages

Present practices in the microscopic counting of phytoplankton to estimate the reliability of results rely on the assumption of a random distribution of taxa in sample preparations. In contrast to that and in agreement with the literature, we show that aggregated distribution is common and can lead to over-optimistic confidence intervals, if estimated according to the shortcut procedure of Lund et al. based on the number of counted cells. We found a good linear correlation between the distribution independent confidence intervals for medians and those for parametric statistics so that 95% confidence intervals can be approximated by using a correction factor of 1.4. Instead, the recommendation to estimate confidence intervals from the total number of counted cells according to Lund et al. should be categorically rejected. We further propose the adoption of real-time confidence intervals during microscopic counting as the criterion to define how long counting should be continued. Then each sample can be counted in its individual way to reach the necessary reliability independent of highly different samples. Such a dynamic counting strategy would be the most significant development in the quality control of phytoplankton counting since the early pioneers established the present counting practices in the late 1950s.

Background Bladder cancer disproportionally affects the communities. While it is the ninth most common cancer in the world, in some parts of Iran including Kerman province it is the most common cancer among men. This study aimed to determine potential risk factors of bladder cancer in Kerman province, Iran. Methods During February to July 2020, in this matched hospital-based case-control study, 100 patients with bladder cancer and 200 healthy individuals (matched in age and sex) were recruited. Socio-demographics status, occupational exposures, common diet, history of drug use and family history of cancer, were collected using a structured questionnaire. Bivariable and multivariable logistic regression were applied and crude and adjusted odds ratios (AOR) along with their 95% confidence intervals (95%CI) were calculated. Data were analyzed using Stata version 14 software. Results Opium consumption, cigarette smoking and low level of income were associated with increased chance of bladder cancer. Compared to never use, use of opium up to 18000 Gram -year was associated with increased chance of bladder cancer (AOR: 6; 95% CI =2.3, 15.5). The chance was higher among those who used opium more than 18,000 Gram - year (AOR: 11.3; 95% CI =2.3, 15.5). In comparison with never smokers, the chance of bladder cancer increased among those who smoked up to 20 pack-year cigarette) (AOR: 3.4; 95%CI= 1.3, 8.9) and those who smoke ≥ 20 pack-year (AOR: 15.8; 95% CI= 5.9, 42.4). Conclusions The observed strong dose-response association between opium consumption, cigarette smoking and bladder cancer highlights the need for extension of harm reduction programs especially in regions with high burden of disease.

Background The rates of smoking among women are rising. Previous studies have shown that smoking is associated with early menopause. However, the association of gynecological cancer, including breast and cervical cancer, with early menopause and smoking, remains unclear. Therefore, this study aimed to determine the association between smoking and early menopause, breast cancer, and cervical cancer. Methods This cross-sectional study used data from the Korean National Health and Nutritional Survey Examination (KHANES) (2016-2018). Early menopause was defined as menopause before 50 years of age. Results A total of 4,481 participants were included in the analysis. There was no association between early menopause and cervical cancer (adjusted odds ratio [aOR]: 1.435, 95% confidence interval [CI]: 0.730-2.821), but women who had experienced early menopause had a significantly higher risk of breast cancer than women who had experienced normal menopause (aOR: 1.683, 95% CI: 1.089-2.602, p=0.019). Early menopause was not associated with an increased risk of breast cancer in ever-smoker (aOR: 0.475, 95% CI: 0.039-5.748), but was associated with a significantly increased risk of breast cancer in never-smokers (aOR: 1.828, 95% CI: 1.171-2.852). Conclusions Early menopause was associated with an increased risk of breast cancer in women who had never smoked, but not in women who had ever smoked.

This research aimed to study the effects of the risk communication program through the Cambodian folk song to prevent Opisthorchiasis-linked cholangiocarcinoma (OV-CCA).We conducted the quasi-experimental research between August and December 2017 in the Cambodian communities, one-fourth of ethnic minorities residing in multicultural areas of Sisaket Province, Thailand. The samples consisted of 94 equally people divided into experimental group and control group. The experimental group included 47 people at-risk of OV-CCA who received the program for 12 weeks, while the control group received regular services. We collected data by using a questionnaire with a reliability of 0.93. Descriptive and inferential statistics were used for data analysis.The study indicated that the socioeconomic information of both groups was not different. The mean scores of all issues (health beliefs, social support, and prevention behavior in the experimental group were higher than those of the control group with statistical significance. Closer inspection showed that the mean difference of the health beliefs was 55.61 points (95%CI: 52.39-57.42, p0.001), social support was 9.09 points (95%CI: 8.12-10.05, p0.001), and prevention behavior was 6.38 points (95%CI: 5.43-7.33, p0.001).Through the Cambodian folk song, the risk communication program by applying the health beliefs and social support to prevent OV-CCA is beneficial for behavior modification in areas with similar cultures.

Restricted mean survival time (RMST) is one measure now used to summarize time-to-event type data, but it has been pointed out that the distribution of differences in RMST deviates markedly from a normal distribution for controlled clinical trials with small sample sizes. Therefore, we conducted a numerical simulation of the RMST in which the one-sample survival time follows a Weibull distribution, comparing eight different confidence intervals combining two types of variance with four types of variable transformations, including no transformation. The evaluation items were the coverage probability and the above and below error probabilities for the true value. The variance types were based on Greenwood's formula and its Kaplan-Meier correction. The arcsine square root transformation, logit transformation, and complementary log-log transformation were used as the variable transformations. When the sample size was small and the event rate was low, the confidence interval of the untransformed RMST tended to have a small coverage probability and to be overestimated. Variance by Kaplan-Meier correction improved the coverage. The problems of coverage and overestimation were also improved by variable transformations, and in particular, applying the logit transformation and the complementary log-log transformation both resulted in substantial improvements. Our study suggested that it is preferable to construct the confidence intervals of RMST using the logit transformation for variances based on Greenwood's formula in small sample size trials. The SAS code to replicate the analyses is available at https://github.com/HiroyaHashimoto/SAS-Programs.

Skewed distributions and inferences concerning quantiles are common in the health and social science researches. And most standard simultaneous inference procedures require the normality assumption. For example, few methods exist for comparing the medians of independent samples or quantiles of several distributions in general. To our knowledge, there is no easy-to-use method for constructing simultaneous confidence intervals for multiple contrasts of quantiles in a one-way layout. In this paper, we develop an asymptotic method for constructing such intervals both for differences and ratios of quantiles and extend the idea to that of right-censored time-to-event data in survival analysis. Small-sample performance of the proposed method and a bootstrap method were assessed in terms of coverage probabilities and average widths of the simultaneous confidence intervals. Good coverage probabilities were observed for most of the distributions considered in our simulations. The proposed methods have been implemented in an R package and are used to analyze two motivating datasets.

We propose a method to objectively establish the initial time period to be removed from the fitting window when, using a mono-exponential model, the kinetics of the fundamental component is determined on breath-by-breath O2 uptake data collected at the onset of a moderate-intensity exercise. Innovative statistical parameters (“Coverage” and “Concordance5%,” applicable on simulated responses) were used to compare its performance with that of other three methods. The proposed method yielded the best “Coverage” and “Concordance5%.”

Women are disproportionately underrepresented in American academic surgery and surgical society leadership; we investigated the proportion of speaking roles held by women across a wide variety of surgical society meetings.Publicly-available data on invited speakers, panelists, and moderators at 23 national surgical societies' annual meetings from 2002 to 2019 were collected. Mixed effects logistic regression was used to evaluate the adjusted trend of gender representation over time for each role.15.9% of invited speakers were women. Adjusted analysis showed an 8% increase in odds of having female speakers per year (OR1.08, p = 0.002, 95%CI 1.03-1.14). 24.4% of moderators and 22.5% of panelists were female; there was increasing trend in adjusted analysis for both moderators (OR1.09, p 0.001, 95%CI 1.07-1.11) and panelists (OR1.13, p 0.001, 95%CI 1.11-1.43).There is a wide range in speaking roles held by women at surgical society meetings, but an encouraging trend towards greater parity was seen overall.

Mitosis is a prognostic factor for cutaneous melanoma (CM), but accurate mitosis detection in CM tissues is difficult. Therefore, the 8th Edition of the American Joint Committee on Cancer staging system has removed the mitotic rate as a category criterion of the tumor T‐category, based on the evidence that the mitotic rate was not an independent prognostic factor for melanoma survival. As single‐nucleotide polymorphisms (SNPs) have been shown to be potential predictors for cutaneous melanoma‐specific survival (CMSS), we investigated the potential prognostic value of SNPs in mitosis‐related pathway genes in CMSS by analyzing their associations with outcomes of 850 CM patients from The University of Texas MD Anderson Cancer Center in a discovery dataset and validated the findings in another dataset of 409 CM patients from the Harvard University Nurses’ Health Study and Health Professionals Follow‐up Study. In both datasets, we identified two SNPs (SDCCAG8 rs10803138 G>A and MAGI2 rs3807694 C>T) as independent prognostic factors for CMSS, with adjusted allelic hazards ratios of 1.49 (95% confidence interval = 1.17‐1.90, P = .001) and 1.45 (1.13‐1.86, P = .003), respectively. Furthermore, their combined unfavorable alleles also predicted a poor survival in both discovery and validation datasets in a dose‐response manner (P trend = .0006 and .0001, respectively). Additional functional analysis revealed that both SDCCAG8 rs10803138 A and MAGI2 rs3807694 T alleles were associated with elevated mRNA expression levels in normal tissues. Therefore, these findings suggest that SDCCAG8 rs10803138 G>A and MAGI2 rs3807694 C>T are independent prognostic biomarkers for CMSS, possibly by regulating the mRNA expression of the corresponding genes involved in mitosis., Mitosis is a prognostic factor for cutaneous melanoma (CM), but accurate mitosis detection in CM tissues is difficult. Therefore, the 8th Edition of the American Joint Committee on Cancer staging system has removed the mitotic rate as a category criterion of the tumor T‐category, based on the evidence that the mitotic rate was not an independent prognostic factor for melanoma survival. Since single‐nucleotide polymorphisms (SNPs) have been shown to be potential predictors for cutaneous melanoma‐specific survival (CMSS), we investigated the potential prognostic value of SNPs in mitosis‐related pathway genes in CMSS by analyzing their associations with outcomes of CM patients from The University of Texas MD Anderson Cancer Center in a discovery dataset and validated the findings in another dataset of CM patients from the Harvard University Nurses’ Health Study and Health Professionals Follow‐up Study. In both datasets, we identified two SNPs (SDCCAG8 rs10803138 G>A and MAGI2 rs3807694 C>T) as independent prognostic factors for CMSS.

The standard multiple imputation technique focuses on parameter estimation and assumes that the parameter estimator is asymptotically normally distributed with a Wald-type confidence interval for the parameter of interest. On the other hand, the Miettinen-Nurminen (MN) method for difference in proportions (Miettinen O, Nurminen M. Stat Med. 1985;4:213-226) constructs the confidence interval using an asymptotic score method and hence is not directly amenable to the standard multiple imputation technique. We propose a multiple imputation analysis that is applicable to the MN method for difference in proportions. We use simulation studies to compare the proposed method with that of Li, Mehrotra and Barnard (LMB), which is based on effective sample sizes (Li X, Mehrotra DV, Barnard J. Stat Med. 2006;25:2107-2124). We show that both methods produce confidence intervals with adequate coverage, while the proposed method produces slightly shorter confidence intervals than the LMB method. In addition, the proposed method is evaluable for all datasets, while the LMB method cannot be used when the imputed cell counts are zero across imputations for a treatment group.

Reference intervals that indicate the anticipated results of clinical chemistry parameters in a healthy background population are essential for the proper interpretation of laboratory data. In the present study, we analysed major trace elements in blood samples from 400 randomly selected members of the general Danish population. Reference intervals were established for trace elements in both whole blood and serum, and associations with major plasma transport proteins were investigated. In the case of a statistically significant correlation, a corresponding protein-adjusted reference interval was established for comparison with the unadjusted interval. While several trace elements correlated with albumin, ferritin and transferrin, the overall impact of transport proteins was minor and resulted in only marginal changes in the reference intervals. In conclusion, the updated reference intervals for trace elements can be employed without adjusting for plasma protein concentrations.

Data envelopment analysis (DEA) is a popular non-parametric approach to examine performance and productivity of airlines; however, it could not provide statistical information such as confidence intervals on the estimated efficiency scores. We combined stochastic frontier analysis and DEA into a single framework to disentangle noise and ‘pure’ inefficiency from the DEA inefficiency scores and accordingly provide confidence intervals for the estimated efficiency scores. Monte-Carlo simulation verified that our novel model is a good alternative for the conventional DEA as well as the bootstrap DEA. Empirical application using Asia-Pacific airlines’ data (2008‒2015) shows that after accounting for the ‘pure’ random errors, the sampled Asia-Pacific airlines performed well during the study period but their ‘pure’ efficiency was declining, hence, there is still room for improvement.

BACKGROUND: Peripartum cardiomyopathy (PPCM) disproportionately affects women of African ancestry. Additionally, clinical outcomes are worse in this subpopulation compared to White women with PPCM. The extent to which socioeconomic parameters contribute to these racial disparities is not known. METHODS: We aimed to quantify the association between area-based proxies of socioeconomic status (SES) and clinical outcomes in PPCM, and to determine the potential contribution of these factors to racial disparities in outcomes. A retrospective cohort study was performed at the University of Pennsylvania Health System, a tertiary referral center serving a population with a high proportion of Black individuals. The cohort included 220 women with PPCM, 55% of whom were Black or African American. Available data included clinical and demographic characteristics as well as residential address georeferenced to US Census-derived block group measures of SES. Rates of sustained cardiac dysfunction (defined as persistent LVEF

To compare clinical features and outcomes in patients with acute myocardial infarction complicated by cardiogenic shock (AMICS) treated in the early experience with Impella percutaneous ventricular assist device and patients treated recently.Since pre-market approval (PMA) of Impella device as treatment for AMICS, use of the device has grown considerably.We retrospectively analyzed 649 AMICS patients treated with perioperative Impella, with 291 patients treated from 2008 to 2014 comprising the early experience cohort and 358 patients treated from 2017 to 2019 comprising the recent experience cohort. The primary end point was risk adjusted in-hospital mortality.Mean age and gender distribution of patients was similar in the two cohorts. The recent cohort had more invasive hemodynamic monitoring (64% vs 46%; P.001) and less use of an intra-aortic balloon pump prior to Impella (15% vs 41%; P.001). Recently treated patients were significantly more likely to receive Impella support prior to PCI (58% vs 44%; P = .005). In-hospital mortality was lower in the recent cohort (48% vs 56%; P = .043). This difference was however no longer significant after risk adjustment (adjusted OR 0.89, 95% CI 0.59-1.34, P = .59). Rates of acute kidney injury, major bleeding, and vascular complications requiring surgery were also significantly lower in the recent cohort.Use of Impella for AMICS during recent years is associated with lower unadjusted in-hospital mortality, which may reflect better patient selection, earlier device implantation, and improved management algorithms. In-depth understanding of these factors may inform the development of future treatment protocols.

Purpose: To date, studies regarding the use of prophylactic cranial irradiation (PCI) versus standard of care (SoC) for patients with non-small cell lung cancer (NSCLC) have not shown a significant effect in terms of overall survival (OS). Additionally, the effect of PCI among high-risk patients has been scarcely studied. The objective of this randomized phase 2 study was to evaluate the role of PCI in a population of patients at high risk for development of brain metastases (BM). Methods and Materials: Eligible patients had histologically confirmed NSCLC without baseline BM, harboring epidermal growth factor receptor mutations, anaplastic lymphoma kinase rearrangements, or elevated carcinoembryonic antigen levels at the time of diagnosis. Participants received systemic therapy according to molecular status, those without progressive disease were then assigned to receive SoC or SoC thorn PCI (25 Gy in 10 fractions). The primary outcome was cumulative incidence of brain metastases (CBM). The secondary endpoints included progression-free survival and OS. Quality of life and neurocognitive function are discussed in a separate article (Clinicaltrials.gov: NCT01603849). Results: From May 2012 to December 2017, 84 patients were enrolled in the study, with 41 patients allocated to receive PCI and 43 received SoC. Patients allocated to receive PCI had a CBM at 24 months of 7% versus 38% in those allocated to the SoC arm. PCI was associated with a hazard ratio of 0.12 (95% confidence interval, 0.035-0.42) for developing BM. A benefit in OS was also observed (64.5 vs 19.8 months; hazard ratio: 0.41 (95% confidence interval, 0.22-0.78; P = .007). Conclusions: Among a selected population at high risk for developing BM, PCI significantly decreased CBM in addition to increasing progression-free survival and OS. To our knowledge, this is the first study to evaluate PCI in epidermal growth factor receptor mutations, anaplastic lymphoma kinase rearrangements, or elevated carcinoembryonic antigen levels in patients with NSCLC, showing a significant improvement in CBM. This relevant information should be of particular importance in the context of patients without access to third-generation targeted agents. Further studies are warranted to ascertain this effect. (C) 2021 Elsevier Inc. All rights reserved.

Purpose This work assessed local and systemic alternations of the tumor immune microenvironment during concurrent chemoradiation therapy (CCRT) of local advanced cervical cancer to estimate the optimal timing for immune therapy in relation to CCRT. Methods and Materials In this single-center prospective clinical trial, 55 patients with stage IIA through IVA cervical cancer were enrolled between December 2016 and November 2017. The median follow-up was 32.1 months. All patients received cisplatin concurrently with external beam radiation therapy combined with high-dose-rate brachytherapy. Tumor tissues and peripheral blood mononuclear cells (PBMCs) were collected before, during and after CCRT. We analyzed the changes in lymphocyte subpopulations, programmed death-1 (PD-1) and programmed cell death ligand 1 (PD-L1) expression, and the T cell receptor (TCR) repertoire that occurred throughout CCRT. Results The frequencies of CD4+ and PD-1+ T cells in PBMCs decreased after the start of CCRT, whereas that of inhibitory regulatory T cells increased. In the tumor tissues, CCRT decreased the numbers of CD4+ and CD8+ T cells and reduced the median percentage of positive cells expressing PD-L1 from 78.1% to 49.8%. As indicated by the numbers of unique clones, the TCRs of PBMCs exhibited greater diversity before CCRT than after CCRT. Greater TCR diversity in PBMCs before CCRT was associated with superior 30-month progression-free survival (hazard ratio [HR], 0.12; 95% confidence interval [CI], 0.04-0.39; P = .001) and overall survival (HR, 0.17; 95% CI, 0.04-0.68; P = .004). Conclusions CCRT for cervical cancer altered the tumor immune microenvironment by reducing CD4+ and CD8+ T lymphocyte populations, PD-1/PD-L1 expression, and TCR diversity. Higher TCR diversity in PBMCs before CCRT resulted in better survival and prognosis, indicating that CCRT might inhibit immune activation. Our results suggest that it might be more effective to administer immune checkpoint inhibitors before CCRT of cervical cancer rather than during or after CCRT.

Purpose Bolus use during postmastectomy radiation therapy doubles the risk of grade 2 and 3 skin toxicity. Despite its unknown benefit, bolus is often prescribed during postmastectomy radiation therapy for patients without skin involvement. Methods and Materials For women with breast cancer receiving photon 3-dimensional conformal radiation therapy, bolus was used routinely for chest walls but was omitted for breast reconstructions by about half of radiation oncologists from 2007 to 2011. Eligible patients had newly diagnosed invasive breast cancers without skin involvement (pT1-4a, any-N, M0) treated with adjuvant or neoadjuvant radiation therapy. For the bolus and no-bolus groups, we compared the cumulative incidence of local recurrence (LR) and locoregional recurrence (LRR) with distant recurrence and death as competing risks and breast cancer mortality (BCM). Multivariable analysis of LR and BCM included stage, subtype, lymphovascular invasion, grade, margin status, beam energy, bolus use, hormone therapy, chemotherapy, and reconstruction. Results Systemic therapy was used for 98% of the 1887 patients. The bolus group had 1569 patients and the no-bolus group had 318 patients. Bolus was used in 51% (281/550) of patients treated with reconstruction and 96% (1288/1337) of patients treated without reconstruction. The 10-year outcomes (95% confidence interval) in patients treated with and without bolus were, respectively: LR 1.9% (1.3-2.7) versus 0.9% (0.3-2.6), LRR 3.1% (2.3-4.0) versus 3.2% (1.6-5.5), and BCM 19.4% (17.3-21.6) versus 18.3% (13.9-23.2). On multivariable analysis, bolus use was not associated with better LR (hazard ratio = 1.4 [0.3-6.4]) or BCM (hazard ratio = 0.8 [0.5-1.2]). Conclusions For patients treated with mastectomy, radiation therapy, and modern systemic therapy, the cumulative incidence of LR was low, with or without bolus. Because bolus use increases toxicity and does not reduce LR or BCM, it should no longer be used routinely for patients without skin involvement who receive systemic therapy.

The trefoil factor family proteins: TFF1, TFF2 and TFF3 are secreted by epithelial cells in the respiratory tract. Here, we explore circulating concentrations of the trefoil factors in relation to lung cancer, age and lung function. We included 751 patients suspected of lung cancer. Lung cancer diagnosis was based on data reported to a national database. Serum TFF1, TFF2 and TFF3 concentrations were measured by ELISA, and spirometry was performed within ±3 days of blood sampling. Forced expiratory volume in the first second (FEV1) in relation to forced vital capacity (FVC), FEV1/FVC (a parameter used to quantify reduced lung function) was recorded. Lung cancer was diagnosed in 163 (22%) patients. Circulating concentrations of TFF3 (p =.021), but not TFF1 and TFF2, were significantly elevated in cancer patients. All three trefoil factors showed an increase in concentration with increasing age (p

PURPOSE: Patients with cancer are presumed to be more vulnerable to COVID-19. We evaluated a screening strategy combining chest computed tomography (CT) and reverse-transcription polymerase chain reaction (RT-PCR) for patients treated with radiation therapy at our cancer center located in a COVID-19 French hotspot during the first wave of the pandemic. METHODS AND MATERIALS: Chest CT images were proposed during radiation therapy CT simulation. Images were reviewed by an expert radiologist according to the COVID-19 Reporting and Data System classification. Nasal swabs with RT-PCR assay were initially proposed in cases of suspicious imaging or clinical context and were eventually integrated into the systematic screening. A dedicated radiation therapy workflow was proposed for COVID-19 patients to limit the risk of contamination. RESULTS: From March 18, 2020 to May 1, 2020, 480 patients were screened by chest CT, and 313 patients had both chest CT and RT-PCR (65%). The cumulative incidence of COVID-19 was 5.4% (95% confidence interval [CI], 3.6-7.8; 26 of 480 patients). Diagnosis of COVID-19 was made before radiation therapy for 22 patients (84.6%) and during RT for 4 patients (15.3%). Chest CT directly aided the diagnosis of 7 cases in which the initial RT-PCR was negative or not feasible, out of a total of 480 patients (1.5%) and 517 chest CT acquisitions. Four patients with COVID-19 at the time of the chest CT screening had a false negative CT. Sensitivity and specificity of chest CT screening in patients with both RT-PCR and chest CT testing were estimated at 0.82 (95% CI, 0.60-0.95) and 0.98 (95% CI, 0.96-0.99), respectively. Adaptation of the radiation therapy treatment was made for all patients, with 7 postponed treatments (median: 5 days; interquartile range, 1.5-14.8). CONCLUSIONS: The benefit of systematic use of chest CT screening during CT simulation for patients undergoing radiation therapy during the COVID-19 pandemic seemed limited.

Prior studies have suggested a higher prevalence of simple renal cysts (SRC) among patients with aortic disease, including abdominal aortic aneurysms (AAA). Thus, the aim of this study was to systematically review all currently available literature and investigate whether patients with AAA are more likely to have SRC.This study was performed according to the PRISMA guidelines. A meta-analysis was conducted with the use of random effects modeling and the I-square was used to assess heterogeneity. Odds ratios (OR) and the corresponding 95% confidence intervals (CI) were synthesized to compare the prevalence of several patients' characteristics between AAA vs. no-AAA cases.Eleven retrospective studies, 9 comparative (AAA vs. no-AAA groups) and 3 single-arm (AAA group), were included in this meta-analysis, enrolling patients (AAA: N = 2,297 vs. no-AAA: N = 35,873) who underwent computed tomography angiography as part of screening or preoperative evaluation for reasons other than AAA. The cumulative incidence of SRC among patients with AAA and no-AAA was 55% (95% CI: 49%-61%) and 32% (95% CI: 22%-42%) respectively, with a statistically higher odds of SRC among patients with AAA (OR: 3.02; 95% CI: 2.01-4.56; P0.001). The difference in SRC prevalence remained statistically significant in a sensitivity analysis, after excluding the study with the largest sample size (OR: 2.71; 95% CI: 1.91-3.84; P0.001).Our meta-analysis demonstrated a 3-fold increased prevalence of SRC in patients with AAA compared to no-AAA cases, indicating that the pathogenic processes underlying SRC and AAA could share a common pathophysiologic mechanism. Thus, patients with SRC could be considered at high risk for AAA formation, potentially warranting an earlier AAA screening.

Objective: To evaluate systematically the association between TBX21 gene polymorphisms (rs17250932, rs2240017, and rs4794067) and the risk of autoimmune diseases in Asian populations. Methods: The Medline, Web of Science, and Chinese Biomedical Literature Database were used to retrieve eligible studies that were published before July 2020. Pooled odds ratios (OR) and 95% confidence intervals (95% CI) were calculated by using the dominant model, heterozygote contrast model, and allelic contrast model. Publication bias was evaluated using contour-enhanced funnel plots and Egger’s regression test. Sensitivity analysis was conducted to assess the robustness of this meta-analysis.Results: A total of 12 eligible studies, including 3834 patients and 4824 healthy controls, were recruited in this meta-analysis. The pooled data demonstrated that TBX21 rs2240017 and rs4794067 polymorphisms were significantly associated with the risk of autoimmune diseases in Asian populations in allelic contrast model (OR: 1.456, 95% CI: 1.131–1.875, P = 0.004; OR: 0.766, 95% CI: 0.615–0.954, P = 0.017), heterozygote comparison model (OR: 1.647, 95% CI: 1.239–2.189, P = 0.001; OR: 0.796, 95% CI: 0.634–0.999, P = 0.049), and dominant model (OR: 1.572, 95% CI: 1.194–2.071, P = 0.004; OR: 0.767, 95% CI: 0.607–0.970, P = 0.027). The G allele of rs2240017 may be a risk factor for autoimmune diseases, and the T allele of rs4794067 may increase the risk of autoimmune diseases. However, we failed to find evidence of the association between TBX21 rs17250932 polymorphism and susceptibility to autoimmune diseases. No publication bias was established in this meta-analysis.Conclusion: This meta-analysis indicated that TBX21 rs2240017 and rs4794067 polymorphism confer susceptibility to autoimmune diseases, but not rs17250932.

Gastrointestinal disturbances are one of the most common issues for endurance athletes during training and competition in the heat. The relationship between typical dietary intake or nutritional interventions and perturbations in or maintenance of gut integrity is unclear. Twelve well-trained male endurance athletes (peak oxygen consumption = 61.4 ± 7.0 ml·kg−1·min−1) completed two trials in a randomized order in 35 °C (heat) and 21 °C (thermoneutral) conditions and kept a detailed nutritional diary for eight consecutive days between the two trials. The treadmill running trials consisted of 15 min at 60% peak oxygen consumption, 15 min at 75% peak oxygen consumption, followed by 8 × 1-min high-intensity efforts. Venous blood samples were taken at the baseline, at the end of each of the three exercise stages, and 1 hr postexercise to measure gut integrity and the permeability biomarker concentration for intestinal fatty-acid-binding protein, lipopolysaccharide, and lipopolysaccharide-binding protein. The runners self-reported gut symptoms 1 hr postexercise and 3 days postexercise. The heat condition induced large (45–370%) increases in intestinal fatty-acid-binding protein, lipopolysaccharide-binding protein, and lipopolysaccharide concentrations compared with the baseline, but induced mild gastrointestinal symptoms. Carbohydrate and polyunsaturated fat intake 24 hr preexercise were associated with less lipopolysaccharide translocation. Protein, carbohydrate, total fat, and polyunsaturated fat intake (8 days) were positively associated with the percentage increase of intestinal fatty-acid-binding protein in both conditions (range of correlations, 95% confidence interval = .62–.93 [.02, .98]). Typical nutrition intake partly explained increases in biomarkers and the attenuation of symptoms induced by moderate- and high-intensity exercise under both heat and thermoneutral conditions.

In sequential testing with binary data, sample size and time to detect a signal are the key performance measures to optimize. While the former should be optimized in Phase III clinical trials, minimizing the latter is of major importance in post-market drug and vaccine safety surveillance of adverse events. The precision of the relative risk estimator on termination of the analysis is a meaningful design criterion as well. This paper presents a linear programming framework to find the optimal alpha spending that minimizes expected time to signal, or expected sample size as needed. The solution enables (a) to bound the width of the confidence interval following the end of the analysis, (b) designs with outer signaling thresholds and inner non-signaling thresholds, and (c) sequential designs with variable Bernoulli probabilities. To illustrate, we use real data on the monitoring of adverse events following the H1N1 vaccination. The numerical results are obtained using the R Sequential package.

The Kling-Gupta efficiency, hereafter referred to as KG efficiency rather than its common abbreviation KGE, proposed by Gupta et al. (2009) has become a widely used metric for evaluating the goodness-of-fit of n-vectors of observations, ỹ=[ỹ1ỹ2…ỹn]⊤, and corresponding model simulations, yθ=y1θy2θ…ynθ⊤. This metric rectifies some of the shortcomings of the coefficient of determination, R2, also known to hydrologists as the efficiency of Nash and Sutcliffe (1970), by using a Euclidean-distance based weighting of the correlation, bias and temporal variability of the observed, ỹ, and simulated, yθ, data. But as the KG efficiency is not borne out of assumptions with respect to the statistical distribution of the residuals, eθ=ỹ-yθ, we cannot formally characterize its uncertainty. The NS efficiency suffers a similar problem, yet, statistical theory postulates that its confidence intervals should follow a beta distribution in certain special cases. Without a formal description of the confidence intervals of the KG efficiency, we cannot (amongst others) quantify parameter uncertainty, compute confidence and prediction limits on simulated model responses, inform decision makers about critical modeling uncertainties, evaluate model adequacy and assess the information content of calibration data. More fundamentally, without confidence intervals we cannot establish whether the KG efficiency is a consistent, efficient and unbiased estimator. In this paper we present an empirical description of the confidence intervals of the KG efficiency. We relate the unknown probability distribution of the KG efficiency to the measurement errors of the training data record, ỹ, and use the bootstrap method to carry out statistical inference. We illustrate our method by application to a simple linear regression function for which the least squares parameter confidence regions are exactly known and two hydrologic models of contrasting complexity. The empirical parameter confidence regions and/or intervals of the KG efficiency are compared to those derived from generalized least squares, objective function contouring and Bayesian analysis using Markov chain Monte Carlo simulation. The marginal parameter distributions of the KG efficiency are generally well described by a normal distribution. Results further confirm that the distribution of the KG efficiency is a complex function of data length and the magnitude, distribution and structure of the measurement errors. This prohibits an analytic description of the empirical confidence regions and/or intervals of the KG efficiency and reiterates the need for the bootstrap method.

Recent research indicates that Cohen’s d follows a non-central t-distribution, even as the central limit theorem approximates normal, contrary to the assumption that effects match the distribution of their test statistic (Cumming, 2012; Kelley, 2007; Smithson, 2003), and little research to date has focused on the variance overlap family of effects. Likewise, meta-analytic techniques also depend on accurate sampling variance estimations of effect sizes. To address this issue, we simulated 1,000 multivariate normal datasets for 1,152 combinations of varying sample sizes, standard deviations, levels, and level correlations. Eta, generalized eta (Olejnik & Algina 2003), omega, and all partial statistics were calculated for between and within subjects ANOVAs. Simulation results indicated an interactive pattern of mean effects and variances across conditions, with variance overlap measures reliably following a beta/gamma/normal distribution. We discuss the impact of design and data type on the measured effect and variance, as well as provide R scripts for simulations to adequately estimate sampling variance for meta-analyses.

Repository of Scripts and Figures For the following Papers: "Semantic and Cognitive Tools to Aid Statistical Science" by Rafi & Greenland, 2020 | https://doi.org/10.1186/s12874-020-01105-9 "To Aid Scientific Inference, Emphasize Unconditional Descriptions of Statistics" by Greenland & Rafi, 2020 | https://arxiv.org/abs/1909.08583 "Technical Issues in the Interpretation of S-values and Their Relation to Other Information Measures" by Greenland & Rafi, 2020 | https://arxiv.org/abs/2008.12991

The "New Statistics" emphasizes effect sizes, confidence intervals, meta-analysis and the use of Open Science practices. We present 3 specific ways in which a New Statistics approach can help improve scientific practice: by reducing over-confidence in small samples, by reducing confirmation bias, and by fostering more cautious judgements of consistency. ** This is the second draft of a pre-print of a manuscript that is under review for a special issue of the American Statistician** on 'Beyond p values'. We welcome your comments and feedback--send it via email or tweet at us: @TheNewStats**

This study seeks to examine how social workers (including: Researchers, academics, practitioners, and students) understand core statistical concepts. We will be attempting to follow the work of Oakes (1986) and Hoekstra et al. (2014) who explored psychologists' interpretation of p-values and confidence intervals - respectively.

This article focuses on the construction of a confidence interval for vaccine efficacy against contagious coronavirus disease-2019 (COVID-19) in a fixed number of events design. Five different approaches are presented, and their performance is investigated in terms of the two-sided coverage probability, non-coverage probability at the lower tail, and expected confidence interval width. Furthermore, the effect of under-sensitivity of diagnosis tests on vaccine efficacy estimation was evaluated. Except for the exact conditional method, the non-coverage probability of the remaining methods may exceed the nominal significance level, e.g., 5%, even for a large number of total confirmed COVID-19 cases. The narrower confidence interval width from the Bayesian, approximate Poisson, and mid-P methods are on the cost of increased instability of coverage probability. When the sensitivity of diagnosis test in the vaccine group is lower than that in the placebo group, the reported vaccine efficacy tends to be overly optimistic. The exact conditional method is preferable to other methods in COVID-19 vaccine efficacy trials when the total number of cases reaches 60; otherwise, mid-p method can be used to obtain a narrower interval width.

Many design experts in the data visualization field espouse minimalism in chart design and condemn the use of visual embellishments and refer to the latter as chart junk that creates distraction and hinders the comprehensibility of charts. Despite this stance against chart junk, many design experts continue to use them in their charts and advocate their incorporation for better engagement, approachability, and memorability. This controversy makes the topic of chart junk highly debatable and raises questions about its benefits, role in visualization and conditions under which it is appropriate to use. Our study seeks to clarify these controversies by replicating the famous study by Bateman et al. (2010) using four different approaches (Study 1 to 4). This not only investigates the controversy surrounding chart junk or visual embellishments in a more thorough manner but also, provides insights on how different approaches in replicability can affect the results of a study. Through this work, we set the framework for further replication and reflect on the replicability issues that we faced in the process. In this part, we conduct a meta-analysis of the reported findings from the 4 different replication studies and compare their results.

Item response theory models the probability of correct responses based on two interacting kinds of parameters: student ability and item difficulty. Whenever we estimate ability, students have a legitimate interest in knowing how certain the estimate is. Confidence intervals are a natural measure of uncertainty. Unfortunately, exact confidence intervals via a likelihood profile technique are computationally demanding. In this paper, we show that confidence intervals can be expressed as the solution to a feature relevance optimization problem. We use this novel formalization to develop two new solvers for confidence intervals and thus achieve speedups by 4-50x while achieving near-indistinguishable results to the state-of-the-art approach.

Between April and July 2020, and, therefore, prior to the broad recommendation of corticosteroids for severe COVID-19, a total of 50 full autopsies were performed in Manaus. We confirmed two invasive cases of aspergillosis through histopathology and gene sequencing (4%) in our autopsy series. The confirmed invasive aspergillosis incidence seems much lower than expected based on the “probable and possible” definitions, and an individualized approach should be considered for each country scenario. Interestingly, a prolonged length of stay in the intensive care unit was not observed in any of the cases. Timely diagnosis and treatment of fungal infection can reduce mortality rates.