Lost in the plot: missing visual elements in Kaplan-Meier plots of phase III oncology trials.

Missing visual elements (MVE) in Kaplan-Meier (KM) curves can misrepresent data, preclude curve reconstruction, and hamper transparency. This study evaluated KM plots of phase III oncology trials. MVE were defined as an incomplete y-axis range or missing number at risk table in a KM curve. Surrogate endpoint KM curves were additionally evaluated for complete interpretability, defined by (1) reporting the number of censored patients and (2) correspondence of the disease assessment interval with the number at risk interval. Among 641 trials enrolling 518 235 patients, 116 trials (18%) had MVE in KM curves. Industry sponsorship, larger trials, and more recently published trials were correlated with lower odds of MVE. Only 3% of trials (15 of 574) published surrogate endpoint KM plots with complete interpretability. Improvements in the quality of KM curves of phase III oncology trials, particularly for surrogate endpoints, are needed for greater interpretability, reproducibility, and transparency in oncology research.

Clinical effectiveness and safety of olaparib in BRCA-mutated, HER2-negative metastatic breast cancer in a real-world setting: final analysis of LUCY.

PURPOSE: The interim analysis of the phase IIIb LUCY trial demonstrated the clinical effectiveness of olaparib in patients with germline BRCA-mutated (gBRCAm), human epidermal growth factor receptor 2 (HER2)-negative metastatic breast cancer (mBC), with median progression-free survival (PFS) of 8.11 months, which was similar to that in the olaparib arm of the phase III OlympiAD trial (7.03 months). This prespecified analysis provides final overall survival (OS) and safety data. METHODS: The open-label, single-arm LUCY trial of olaparib (300 mg, twice daily) enrolled adults with gBRCAm or somatic BRCA-mutated (sBRCAm), HER2-negative mBC. Patients had previously received a taxane or anthracycline for neoadjuvant/adjuvant or metastatic disease and up to two lines of chemotherapy for mBC. RESULTS: Of 563 patients screened, 256 (gBRCAm, n = 253; sBRCAm, n = 3) were enrolled. In the gBRCAm cohort, median investigator-assessed PFS (primary endpoint) was 8.18 months and median OS was 24.94 months. Olaparib was clinically effective in all prespecified subgroups: hormone receptor status, previous chemotherapy for mBC, previous platinum-based chemotherapy (including by line of therapy), and previous cyclin-dependent kinase 4/6 inhibitor use. The most frequent treatment-emergent adverse events (TEAEs) were nausea (55.3%) and anemia (39.2%). Few patients (6.3%) discontinued olaparib owing to a TEAE. No deaths associated with AEs occurred during the study treatment or 30-day follow-up. CONCLUSION: The LUCY patient population reflects a real-world population in line with the licensed indication of olaparib in mBC. These findings support the clinical effectiveness and safety of olaparib in patients with gBRCAm, HER2-negative mBC. CLINICAL TRIAL REGISTRATION: Clinical trials registration number: NCT03286842.

Beyond Hormones: Investigating the Impact of Progesterone Receptor Membrane Component 1 in Lung Adenocarcinoma.

Progesterone Receptor Membrane Component 1 (PGRMC1) is a candidate oncogene with a prominent involvement in the pathogenesis of diverse cancers (ovarian, thyroid, breast, colon, head, and neck). Our study ascertains the ability of PGRMC1 to influence WNT members in the non-small cell lung cancer subtype-lung adenocarcinoma (LUAD) and participates in augmented cell proliferation and migration. Both computational and in vitro experimental analyses were performed in this study. Gene silencing, in vitro assays, gene expression & and protein expression studies were performed to ascertain the role of PGRMC1 in LUAD cells. The computational analysis, PGRMC1 gene level expression was analysed using the microarray gene expression omnibus datasets (GSE27262; GSE18842) to compare LUAD tumours and normal tissues. Concurrently, the gene expression profiling interactive analysis of PGRMC1 and Kaplan-Meier survival analysis revealed a decreasing patient survival rate with an increasing PGRMC1 gene expression in LUAD tumour samples. Interestingly, the experimental gene silencing studies were conducted in vitro (si-PGRMC1 Vs si-Control) to understand the essential role of PGRMC1 in regulating WNT-associated genes (WNT1, WNT5A, and WNT11). Comparative experimental cell migration and spheroid formation assays (si-PGRMC1 Vs si-Control) in vitro showed a strong association between PGRMC1 and LUAD. In vitro expression analysis using real-time PCR and western blot further confirmed the connecting link between PGRMC1 and WNT5A compared to other WNT member genes (WNT1 and WNT11) in LUAD. The computational and experimental analyses agreed with one another.

Patterns and treatment outcomes of primary bone tumors in children treated at tertiary referral hospital, Ethiopia.

BACKGROUND: Bone tumors account for approximately 6% of all cancers in children. Malignant bone tumors, commonly occurring in children and adolescents, are associated with high mortality and morbidity. The overall survival of children with primary malignant bone tumors is affected by the stage of disease, time of diagnosis, and treatment response. Despite advanced treatment modalities with chemotherapy, surgery, and radiotherapy, bone tumor is the third leading cause of death in children with malignancy. Patients with metastatic disease at diagnosis have poor outcomes compared to localized disease at presentation. The 5-year Overall Survival and event-free survival in children with primary malignant bone tumors were 85.2% and 69.2%. The study aimed to assess the clinicopathological profile and treatment outcomes of children with primary malignant bone tumors in our setup. MATERIALS AND METHODS: A hospital-based cross-sectional study was conducted on 95 children who met the inclusion criteria through structured questionnaire. The collected data were analyzed using a statistical package for social sciences (SPSS) version 25. P-value < 0.05 was considered to be statistically significant. Kaplan Meier survival estimate was used for overall and event-free survival analysis. RESULTS: A total of ninety-five patients met the study inclusion criteria and the median age at diagnosis with primary malignant bone tumors was 10 years, with an interquartile range of 8-12 years. The duration of the illness from the onset of symptoms to the oncologic treatment center ranges from three weeks to 2 years with a mean duration of five months. Swelling was the commonest presenting symptom accounting for 95.8% (n = 91). Lower extremity was the commonest primary site of involvement accounting for 55.8% (n = 53) of children with primary malignant bone tumors. Osteosarcoma was the commonest malignant bone tumor constituted 66.3% (n = 63), followed by Ewing sarcoma at 33.7% (n = 32). About 41.2% (n = 39) of children had metastatic disease at presentation and the lung was the commonest site of distant metastasis. The Kaplan Meier survival estimate analysis showed the 1-year and 5-year overall survival probabilities for all pediatric primary malignant bone tumor patients were 65% (95% CI: 0.3-0.56) and 38% (95% CI:0.19-0.47) respectively. The 1-year and 5-year event-free survival probabilities were 55% (95% CI: 0.32-0.73) and 33% (95% CI: 0.10-0.59). The stage of the disease at presentation had a significant association with the outcome (p = 0.023). CONCLUSION: Our study showed the mean duration of the illness from the onset of symptoms to the oncologic treatment center was 5 months ranging from 3 weeks to 2 years. More than one-third of the presented with metastatic disease at presentation. The 1-year and 5-year overall survival (OS) probabilities of children with primary malignant bone tumors were low in our setup compared to other studies.

Assessing the influence of graft loss on 4-year patient survival after simultaneous pancreas-kidney transplantation: Kaplan-Meier versus Competing Risk Analysis model.

BACKGROUND: Graft loss increases the risk of patient death after simultaneous pancreas-kidney (SPK) transplantation. The relative risk of each graft failure is complex due to the influence of several competing events. METHODS: This retrospective, single-center study compared 4-year patient survival according to the graft status using Kaplan-Meier (KM) and Competing Risk Analysis (CRA). Patient survival was also assessed according to five eras (Era 1: 2001-2003; Era 2: 2004-2006; Era 3: 2007-2009; Era 4: 2010-2012; Era 5: 2012-2015). RESULTS: Between 2000 and 2015, 432 SPK transplants were performed. Using KM, patient survival was 86.5% for patients without graft loss (n = 333), 93.4% for patients with pancreas graft loss (n = 46), 43.7% for patients with kidney graft loss (n = 16), and 25.4% for patients with pancreas and kidney graft loss (n = 37). Patient survival was underestimated using KM versus CRA methods in patients with pancreas and kidney graft losses (25.4% vs. 36.2%), respectively. Induction with lymphocyte depleting antibodies was associated with 81% reduced risk (HR.19, 95% CI.38-.98, p = .0048), while delayed kidney function (HR 2.94, 95% CI 1.09-7.95, p = .033) and surgical complications (HR 2.94, 95% CI 1.22-7.08, p = .016) were associated with higher risk of death. Four-year patient survival increased from Era 1 to Era 5 (79% vs. 87.9%, p = .047). CONCLUSION: In this cohort of patients, kidney graft loss, with or without pancreas graft loss, was associated with higher mortality after SPK transplantation. Compared to CRA, the KM model underestimated survival only among patients with pancreas and kidney graft losses. Patient survival increased over time.

SurvdigitizeR: an algorithm for automated survival curve digitization.

BACKGROUND: Decision analytic models and meta-analyses often rely on survival probabilities that are digitized from published Kaplan-Meier (KM) curves. However, manually extracting these probabilities from KM curves is time-consuming, expensive, and error-prone. We developed an efficient and accurate algorithm that automates extraction of survival probabilities from KM curves. METHODS: The automated digitization algorithm processes images from a JPG or PNG format, converts them in their hue, saturation, and lightness scale and uses optical character recognition to detect axis location and labels. It also uses a k-medoids clustering algorithm to separate multiple overlapping curves on the same figure. To validate performance, we generated survival plots form random time-to-event data from a sample size of 25, 50, 150, and 250, 1000 individuals split into 1,2, or 3 treatment arms. We assumed an exponential distribution and applied random censoring. We compared automated digitization and manual digitization performed by well-trained researchers. We calculated the root mean squared error (RMSE) at 100-time points for both methods. The algorithm's performance was also evaluated by Bland-Altman analysis for the agreement between automated and manual digitization on a real-world set of published KM curves. RESULTS: The automated digitizer accurately identified survival probabilities over time in the simulated KM curves. The average RMSE for automated digitization was 0.012, while manual digitization had an average RMSE of 0.014. Its performance was negatively correlated with the number of curves in a figure and the presence of censoring markers. In real-world scenarios, automated digitization and manual digitization showed very close agreement. CONCLUSIONS: The algorithm streamlines the digitization process and requires minimal user input. It effectively digitized KM curves in simulated and real-world scenarios, demonstrating accuracy comparable to conventional manual digitization. The algorithm has been developed as an open-source R package and as a Shiny application and is available on GitHub: https://github.com/Pechli-Lab/SurvdigitizeR and https://pechlilab.shinyapps.io/SurvdigitizeR/ .

Augmentation Therapy for Severe Alpha-1 Antitrypsin Deficiency Improves Survival and Is Decoupled from Spirometric Decline-A Multinational Registry Analysis.

Rationale: Intravenous plasma-purified alpha-1 antitrypsin (IV-AAT) has been used as therapy for alpha-1 antitrypsin deficiency (AATD) since 1987. Previous trials (RAPID and RAPID-OLE) demonstrated efficacy in preserving computed tomography of lung density but no effect on FEV1. This observational study evaluated 615 people with severe AATD from three countries with socialized health care (Ireland, Switzerland, and Austria), where access to standard medical care was equal but access to IV-AAT was not. Objectives: To assess the real-world longitudinal effects of IV-AAT. Methods: Pulmonary function and mortality data were utilized to perform longitudinal analyses on registry participants with severe AATD. Measurements and Main Results: IV-AAT confers a survival benefit in severe AATD (P < 0.001). We uncovered two distinct AATD phenotypes based on an initial respiratory diagnosis: lung index and non-lung index. Lung indexes demonstrated a more rapid FEV1 decline between the ages of 20 and 50 and subsequently entered a plateau phase of minimal decline from 50 onward. Consequentially, IV-AAT had no effect on FEV1 decline, except in patients with a Global Initiative for Chronic Obstructive Lung Disease (GOLD) stage 2 lung index. Conclusions: This real-world study demonstrates a survival advantage from IV-AAT. This improved survival is largely decoupled from FEV1 decline. The observation that patients with severe AATD fall into two major phenotypes has implications for clinical trial design where FEV1 is a primary endpoint. Recruits into trials are typically older lung indexes entering the plateau phase and, therefore, unlikely to show spirometric benefits. IV-AAT attenuates spirometric decline in lung indexes in GOLD stage 2, a spirometric group commonly outside current IV-AAT commencement recommendations.

Clinical Longevity of Obturators in Patients with Jaw Defects: a Retrospective Cohort Study.

OBJECTIVES: The primary objective of the present retrospective clinical study was to determine the survival time of obturators while analyzing possible influencing factors. MATERIALS AND METHODS: This retrospective clinical cohort study analyzed the influence of various clinical factors on the survival probability of obturators and their follow-up outcomes using Kaplan‒Meier analysis. RESULTS: A total of 76 patients with 115 obturators were included in the study (47 men and 29 women, mean age 58.1 ± 18.1 years). The mean observation time was 3.0 ± 4.5 years (maximum 26.3 years). A total of 40.9% (47) of all obturators observed had to be replaced. The survival rate after 5 years was 79.5% for telescopic-crown-retained tooth-supported obturators, 86.9% for telescopic-crown-retained implant-supported obturators, 58.8% for removable full denture obturators, 22.1% for clasp-retained obturators and 0.0% for splints. The type of attachment, attendance at a regular follow-up and defect cause significantly influenced the survival of the obturators (p < .05). CONCLUSIONS: The findings obtained in this study support the recommendation of using implant-supported obturators. Telescopic-crown attachments, either tooth- or implant-supported, seem to be favorable in terms of survival time. Attendance at a strict follow-up program seems to have a major influence on the longevity of the obturators. CLINICAL RELEVANCE: The use of implant-supported obturators to cover permanent oral and maxillofacial defects is highly recommended. Additionally, the use of telescopic-crown attachments seems to be favorable in terms of survival time. Clasp-retained obturators and surgical splints should be used primarily for temporary restorations due to their shorter survival times.

Indications, Clinical Outcomes, and Re-Revisions Following Revision Total Hip Arthroplasty - Does Age Matter?

BACKGROUND: Younger age is associated with increased revision incidence following primary total hip arthroplasty, though the association between age and repeat revision following revision total hip arthroplasty (rTHA) has not been described. This study aimed to describe the incidences and indications for subsequent revision (re-revision) following rTHA based on age. METHODS: Patients undergoing aseptic rTHA from 2011 to 2021 with minimum 1-year follow-up were retrospectively reviewed. Patients were stratified into 3 groups based on age at the time of index rTHA (ie, <55 years, 55 to 74 years, and >74 years). Perioperative characteristics, complications, and re-revisions were compared between groups. RESULTS: Of 694 included rTHAs, those in the >74 age group were more likely to undergo rTHA for periprosthetic fracture (P < .001) while those in the <55 age group were more likely to undergo rTHA for metallosis/taper corrosion (P = .028). Readmissions (P = .759) and emergency department visits (P = .498) within 90 days were comparable across ages. Rates of re-revision were comparable at 90 days (P = .495), 1 year (P = .443), and 2 years (P = .204). Kaplan-Meier analysis of all-cause re-revision at latest follow-up showed a nonstatistically significant trend toward increasing re-revisions in the <55 and 55 to 74 age groups. Using logistic regressions, smoking and index rTHA for instability were independently associated with re-revision, while age at index surgery was not. CONCLUSIONS: While indications for rTHA differ across age groups, rates of 2-year re-revision are statistically comparable between groups. Further studies are warranted to understand the association between age, activity, and re-revision rates after 5 years postoperatively.

Survival Analysis Without Sharing of Individual Patient Data by Using a Gaussian Copula.

Cox regression and Kaplan-Meier estimations are often needed in clinical research and this requires access to individual patient data (IPD). However, IPD cannot always be shared because of privacy or proprietary restrictions, which complicates the making of such estimations. We propose a method that generates pseudodata replacing the IPD by only sharing non-disclosive aggregates such as IPD marginal moments and a correlation matrix. Such aggregates are collected by a central computer and input as parameters to a Gaussian copula (GC) that generates the pseudodata. Survival inferences are computed on the pseudodata as if it were the IPD. Using practical examples we demonstrate the utility of the method, via the amount of IPD inferential content recoverable by the GC. We compare GC to a summary-based meta-analysis and an IPD bootstrap distributed across several centers. Other pseudodata approaches are also considered. In the empirical results, GC approximates the utility of the IPD bootstrap although it might yield more conservative inferences and it might have limitations in subgroup analyses. Overall, GC avoids many legal problems related to IPD privacy or property while enabling approximation of common IPD survival analyses otherwise difficult to conduct. Sharing more IPD aggregates than is currently practiced could facilitate "second purpose"-research and relax concerns regarding IPD access.

Comparison of nonparametric estimators of the expected number of recurrent events.

We compare the performance of nonparametric estimators for the mean number of recurrent events and provide a systematic overview for different recurrent event settings. The mean number of recurrent events is an easily interpreted marginal feature often used for treatment comparisons in clinical trials. Incomplete observations, dependencies between successive events, terminating events acting as competing risk, or gaps between at risk periods complicate the estimation. We use survival multistate models to represent different complex recurrent event situations, profiting from recent advances in nonparametric estimation for non-Markov multistate models, and explain several estimators by using multistate intensity processes, including the common Nelson-Aalen-type estimators with and without competing mortality. In addition to building on estimation of state occupation probabilities in non-Markov models, we consider a simple extension of the Nelson-Aalen estimator by allowing for dependence on the number of prior recurrent events. We pay particular attention to the assumptions required for the censoring mechanism, one issue being that some settings require the censoring process to be entirely unrelated while others allow for state-dependent or event-driven censoring. We conducted extensive simulation studies to compare the estimators in various complex situations with recurrent events. Our practical example deals with recurrent chronic obstructive pulmonary disease exacerbations in a clinical study, which will also be used to illustrate two-sample-inference using resampling.

On the role of Volterra integral equations in self-consistent, product-limit, inverse probability of censoring weighted, and redistribution-to-the-right estimators for the survival function.

This paper reconsiders several results of historical and current importance to nonparametric estimation of the survival distribution for failure in the presence of right-censored observation times, demonstrating in particular how Volterra integral equations help inter-connect the resulting estimators. The paper begins by considering Efron's self-consistency equation, introduced in a seminal 1967 Berkeley symposium paper. Novel insights provided in the current work include the observations that (i) the self-consistency equation leads directly to an anticipating Volterra integral equation whose solution is given by a product-limit estimator for the censoring survival function; (ii) a definition used in this argument immediately establishes the familiar product-limit estimator for the failure survival function; (iii) the usual Volterra integral equation for the product-limit estimator of the failure survival function leads to an immediate and simple proof that it can be represented as an inverse probability of censoring weighted estimator; (iv) a simple identity characterizes the relationship between natural inverse probability of censoring weighted estimators for the survival and distribution functions of failure; (v) the resulting inverse probability of censoring weighted estimators, attributed to a highly influential 1992 paper of Robins and Rotnitzky, were implicitly introduced in Efron's 1967 paper in its development of the redistribution-to-the-right algorithm. All results developed herein allow for ties between failure and/or censored observations.

RKHS-based covariate balancing for survival causal effect estimation.

Survival causal effect estimation based on right-censored data is of key interest in both survival analysis and causal inference. Propensity score weighting is one of the most popular methods in the literature. However, since it involves the inverse of propensity score estimates, its practical performance may be very unstable, especially when the covariate overlap is limited between treatment and control groups. To address this problem, a covariate balancing method is developed in this paper to estimate the counterfactual survival function. The proposed method is nonparametric and balances covariates in a reproducing kernel Hilbert space (RKHS) via weights that are counterparts of inverse propensity scores. The uniform rate of convergence for the proposed estimator is shown to be the same as that for the classical Kaplan-Meier estimator. The appealing practical performance of the proposed method is demonstrated by a simulation study as well as two real data applications to study the causal effect of smoking on survival time of stroke patients and that of endotoxin on survival time for female patients with lung cancer respectively.

Survival Probability in Multidrug Resistant Pulmonary Tuberculosis Patients in a South Indian Region.

Background: Drug-resistant tuberculosis is a burgeoning threat to public health requiring novel strategies to combat the infection. Although national tuberculosis elimination programs focus on improving health services, challenges in eradicating tuberculosis still exist. Factors attributing to unfavorable outcomes are unknown in Warangal district of Telangana state. Methods: This study included 296 patients diagnosed with multidrug-resistant pulmonary tuberculosis. The study participants followed up for a maximum of 20 months to determine treatment outcomes. Statistical applications of Kaplan-Meier curve and log-rank test used to find the survival probabilities in subgroups. Results: The survival of multidrug-resistant pulmonary tuberculosis patients was ascertained, in male and female patients, aged between 31 and 50 years. Resistance to rifampicin was prominent. The study found a survival rate of 76.68% and a mortality rate of 23.31%. The log-rank test revealed a significant difference in survival in subcategories with and without comorbidities (P = .03), non-adherence to treatment (P = .0001), treatment duration (P = .02), regimens (P = .01), and grading of radiograph (P = .0001). Conclusion: This study identified factors that influenced the survival probability of multidrug-resistant pulmonary tuberculosis patients, including comorbidities, weight band, non-adherence to treatment, treatment duration, regimens, and grading of radiograph. These findings emphasize the need for enhanced management strategies to improve treatment outcomes.

Post hoc survival analyses using RNAseq data: handle with care.

With the advent of next-generation sequencing technologies, there has been a dramatic increase in the availability of paired clinical and transcriptomic data in a variety of disease states. For basic science researchers, this has provided a valuable opportunity for querying the impact of the transcript levels of a gene on disease survival in humans. However, there are a multitude of methodological and technical considerations to evaluate before embarking on these analyses. Herein, we provide a brief description of statistical considerations involved in these analyses, geared toward basic scientists who may not necessarily routinely use such statistical models as part of their studies.

RSK4 confers paclitaxel resistance to ovarian cancer cells, which is resensitized by its inhibitor BI-D1870.

Many ovarian cancers initially respond well to chemotherapy, but often become drug-resistant after several years. Therefore, analysis of drug resistance mechanisms and overcoming resistance are urgently needed. Paclitaxel is one of the first-choice and widely-used drugs for ovarian cancer, but like most drugs, drug resistance is observed in subsequent use. RSK4 is known as a tumor-suppressor, however, it has increasingly been reported to lead to drug resistance. Here, we found that RSK4 expression was elevated in paclitaxel-resistant ovarian cancer cells using DNA microarray, quantitative real-time PCR, and western blotting analysis. We examined the contribution of RSK4 to paclitaxel resistance and found that paclitaxel sensitivity was restored by RSK inhibitor co-treatment. We analyzed the mechanism by which resistance is developed when RSK4 level is elevated, and accelerated phosphorylation of the downstream translation factor eIF4B was discovered. In the Kaplan-Meier plot, the overall survival time was longer with RSK4 high, supporting its role as a tumor suppressor, as in previous findings, but the tendency was reversed when focusing on paclitaxel treatment. In addition, RSK4 levels were higher in non-responders than in responders in the ROC plotter. Finally, external expression of RSK4 in ovarian cancer cells increased the cell viability under paclitaxel treatment. These findings suggest that RSK4 may contribute to paclitaxel resistance, and that co-treatment with RSK4 inhibitors is effective treatment of paclitaxel-resistant ovarian cancer in which RSK4 is elevated.

Gamma Knife radiosurgery for meningiomas of the confluence of the falx and tentorium.

PURPOSE: Meningiomas arising from the confluence of the falx and tentorium (CFT) are a rare and challenging subset of meningiomas. Gamma Knife radiosurgery (GKRS) is well-established as a safe and effective management strategy for intracranial meningiomas, but its role in treating CFT meningiomas is not well-described. This paper reports the largest series focused exclusively on the outcomes of GKRS for CFT meningiomas. METHODS: We retrospectively identified 20 CFT meningiomas out of 2031 meningioma patients who underwent GKRS at our institution between 1987 and 2021. Tumor control, overall survival (OS), and complications were recorded and analyzed. The median tumor margin dose was 13 Gy at the 50% isodose line. The median tumor volume treated was 4.4 cc (IQR 3.5-7.7). The median patient age was 58 years (range 33-83), the median MRI surveillance duration was 59 months (IQR 34-92), and the median overall follow-up duration was 92 months (IQR 42-201). RESULTS: The local tumor control rate (PFS) at 5 and 10-years were 100% (N=10) and 83% (N=4), respectively. Eight patients had stable tumor volumes and 11 patients had regression. One patient with a twice-operated tumor had delayed progression at 7.5 years and was retreated with GKRS. No patient had adverse radiation effects during the period of MRI surveillance. The 5 and 10-year OS were 100% (N=13) and 100% (N=7), respectively. CONCLUSIONS: GKRS is a valuable therapeutic strategy for patients with newly diagnosed CFT meningiomas or progressive residual tumors after surgical resection.

Multiparametric MRI-based VI-RADS: can it predict 1- to 5-year recurrence of bladder cancer?

OBJECTIVES: To evaluate whether Vesical Imaging-Reporting And Data System (VI-RADS) scores based on multiparametric MRI (mp-MRI) can predict bladder cancer (BCa) recurrence. METHODS: In this retrospective study, 284 patients with pathologically confirmed bladder neoplasms from November 2011 to October 2020 were included. Two radiologists blindly and independently scored mp-MRI scans according to VI-RADS. Scoring inconsistency was resolved in consensus. The latest follow-up was completed in December 2022. Pearson's correlation analyses, independent-sample t-tests, and receiver operating characteristic analyses were performed to assess the efficacy of VI-RADS score for the 1- to 5-year recurrence prognostication. RESULTS: Based on the latest follow-up, 37 (of 284, 13.0%), 69 (of 284, 24.3%), 70 (of 234, 29.9%), 72 (of 190, 37.9%), and 63 (of 135, 46.7%) patients had cancer recurrence at 1- to 5-year follow-up, respectively. VI-RADS scores showed significantly intergroup differences between recurrent and nonrecurrent cases during 1- to 4-year surveillance (p < 0.05). The recurrence-free survival was significantly higher in patients with VI-RADS scores of 1 or 2, compared to those with scores of 3, 4, or 5 (p < 0.05). Areas under the receiver operating characteristic curves for 1- to 5-year recurrence prediction were 0.744, 0.686, 0.656, 0.595, and 0.536, respectively. VI-RADS score of 3 or more was the threshold for 1-year recurrence assessment, and VI-RADS more than 3 was the cutoff for 2-year recurrence prediction. CONCLUSION: VI-RADS score has potential in preoperative prognostication of BCa recurrence, but its predictive power decreases over time. CLINICAL RELEVANCE STATEMENT: VI-RADS has potential in bladder cancer recurrence assessment, but its prognostic value decreases over time. Patients with VI-RADS ≥ 3 may be more likely to recur in 1 or 2 years postoperatively, thus should be performed with intensive surveillances. KEY POINTS: • VI-RADS scores had significant differences in 1- to 4-year recurrent and nonrecurrent patient groups. • Patients with VI-RADS scores of ≤ 2 showed more favorable recurrence-free survival outcomes. • The prognostic value of VI-RADS score decreased over time for bladder cancer recurrence prediction.

Antithrombotic and Lipid Lowering Therapy is Associated With Improved Survival After Vascular Surgery: A Population Based Study From Norway.

OBJECTIVE: This population based retrospective cohort study aimed to investigate the association between combined treatment with lipid lowering drugs and antiplatelet or anticoagulation therapy and long term survival following vascular surgery in Norway. METHODS: The study included all patients who were registered for the treatment of carotid stenosis, abdominal aortic aneurysm (AAA), and atherosclerotic lower extremity arterial disease (LEAD) in the Norwegian Registry for Vascular Surgery between 2015 and 2019 and who were discharged alive. Clinical and medication details were retrieved from the register. Survival was assessed with Kaplan-Meier analysis and a multivariable Cox regression model. Stratification was according to treatment group, patient sex, and if patients received the recommended medications or not. Recommended medications were defined as lipid lowering drugs, usually statins, and antiplatelets, or sometimes anticoagulants, when comorbidity indicated anticoagulation therapy. RESULTS: In total, 15 810 patients had LEAD, 4 080 patients AAA, and 2 194 patients had carotid stenosis. In all treatment groups, survival was superior for patients who used the recommended medications upon discharge. The difference was greatest in patients with LEAD with mean survival periods of 4.33 (95% CI 4.29 - 4.36) and 3.7 (95% CI 3.64 - 3.77) years in patients discharged with and without the recommended medications, respectively (p < .001). The mean survival periods were 4.67 (95% CI 4.61 - 4.73) and 4.34 (95% CI 4.24 - 4.44) years in patients with AAA discharged with and without the recommended medications, respectively (p < .001). Cox regression analysis showed a statistically significantly lower mortality rate for patients discharged with the recommended medications for LEAD (HR 0.58; p < .001) and AAA (HR 0.57; p < .001). CONCLUSION: The recommended medications were associated with improved survival in all treatment groups and both sexes. The survival difference was statistically significant in patients with LEAD and AAA. Patients with LEAD had the greatest improvement; therefore, the recommended secondary prophylaxis is especially important in these patients.

Extrapolating empirical long-term survival data: the impact of updated follow-up data and parametric extrapolation methods on survival estimates in multiple myeloma.

BACKGROUND: In economic evaluations, survival is often extrapolated to smooth out the Kaplan-Meier estimate and because the available data (e.g., from randomized controlled trials) are often right censored. Validation of the accuracy of extrapolated results can depend on the length of follow-up and the assumptions made about the survival hazard. Here, we analyze the accuracy of different extrapolation techniques while varying the data cut-off to estimate long-term survival in newly diagnosed multiple myeloma (MM) patients. METHODS: Empirical data were available from a randomized controlled trial and a registry for MM patients treated with melphalan + prednisone, thalidomide, and bortezomib- based regimens. Standard parametric and spline models were fitted while artificially reducing follow-up by introducing database locks. The maximum follow-up for these locks varied from 3 to 13 years. Extrapolated (conditional) restricted mean survival time (RMST) was compared to the Kaplan-Meier RMST and models were selected according to statistical tests, and visual fit. RESULTS: For all treatments, the RMST error decreased when follow-up and the absolute number of events increased, and censoring decreased. The decline in RMST error was highest when maximum follow-up exceeded six years. However, even when censoring is low there can still be considerable deviations in the extrapolated RMST conditional on survival until extrapolation when compared to the KM-estimate. CONCLUSIONS: We demonstrate that both standard parametric and spline models could be worthy candidates when extrapolating survival for the populations examined. Nevertheless, researchers and decision makers should be wary of uncertainty in results even when censoring has decreased, and the number of events has increased.