Cumulative Distribution Function Research Articles

Rural households' livelihood transitions in China: processes, drivers and outcomes

PurposeThis study aims to comprehensively examine the transitions in household livelihood strategies within rural China, including the underlying processes, drivers and outcomes.Design/methodology/approachThis study uses two waves (2010 and 2018) of longitudinal data from the China Family Panel Studies (CFPS), employing latent cluster analysis, regression models and cumulative distribution function within a dynamic household livelihood strategy framework.FindingsThe results show that (1) households’ livelihood strategies can be categorized into four distinct types, i.e. agricultural dominated, agricultural dominated with non-agricultural supplementation, non-agricultural dominated with agricultural supplementation and employment oriented. (2) During 2010–2018, approximately 60% of households underwent transitions in their livelihoods, encompassing both upward and downward trajectories, with a prevalence of upward transitions. (3) Various forms of livelihood capital significantly contribute to upward transitions, while the availability of land resources and exposure to shocks impede the potential for upward mobility. (4) The transition towards non-agricultural livelihood strategies by households leads to a notable enhancement in their livelihood welfare.Research limitations/implicationsIn the context of urbanization, industrialization and globalization, rural areas in China are undergoing a gradual socioeconomic transformation, which has also led to changes in rural households’ livelihood strategies. Nevertheless, a dearth of empirical investigation exists regarding the dynamics of rural households’ livelihood strategies, the determinants behind such transitions and the resulting outcomes on their livelihoods. A comprehensive understanding of livelihood transitions can provide valuable insights for policymakers in their endeavors to promote rural revitalization in China.Originality/valueBased on the nationwide representative datasets in China, it examines the micro-level livelihood transitions of rural households within the broader context of socioeconomic transformation that presents both opportunities and challenges, as well as vulnerable contexts, shaped by various government policies. This exploration would offer valuable theoretical and empirical evidence to advance our understanding of the process, driver and outcome of rural households’ livelihood transition in developing countries.

An Effective Method for Estimating the Population Mean That Utilizes Dual Auxiliary Information

To improve the effectiveness of population estimators, researchers have recently implemented dual supplementary information. They employed traditional rankings, the empirical cumulative distribution function, and indicator functions as supplementary sources of information in their analysis. An improved family of population mean estimators is introduced in this article, which utilizes the relative ranks of the auxiliary information’s configurations to incorporate the relevant information. A first-order approximation is employed to derive the mathematical expressions for the bias and the mean-squared error (MSE) of the proposed family of estimators. The empirical analysis is investigated to demonstrate the practicality of the proposed estimators in real-world scenarios. Additionally, the theoretical conclusions are effectively validated by the Monte Carlo simulation integration. Our results unequivocally indicate that the proposed family of estimators surpasses their current counterparts.

Maximum non-bounded difference method for overbounding Global Navigation Satellite System errors

AbstractGlobal Navigation Satellite Systems (GNSS) support numerous applications, including mission-critical ones that require high integrity for safe operations such as air, maritime, and land-based navigation. These applications require ensuring the upper bound of the positioning computation, including overbounding any assumptions made in positioning algorithms. One of the main assumptions in the GNSS positioning algorithm is that the error follows a Probability Density Function (PDF), widely assumed to be Gaussian. This assumption should be overbounded to ensure safety. Two mathematical definitions of distribution overbounding have been proposed: Cumulative Distribution Function (CDF) overbounding and paired overbounding. Achieving these definitions has been an open problem for the past 20 years, and to date, no methods have effectively achieved either definition in multimode datasets. This paper proposes the first overbounding method, the Maximum non-Bounded Difference (MnBD) method, capable of achieving both definitions. Its effectiveness is assessed by comparison with the combined CDF bounding and paired overbounding approach. The results show that the MnBD method successfully achieves overbounding in both real datasets and 1000 simulated multimode data, tested on Gaussian and Generalized Extreme Value (GEV) distributions. The latter demonstrates MnBD’s ability to handle asymmetric distributions. The developed approach can be utilized in overbounding the GNSS error at the system level and user level to ensure the system integrity.

Fragility of Highway Embankments Exposed to Permanent Deformations Due to Underlying Fault Rupture

Seismic risk expresses the expected degree of damage and loss following a catastrophic event. An efficient tool for assessing the seismic risk of embankments is fragility curves. This research investigates the influence of embankment’s geometry, the depth of rupture occurrence, and the underlying sandy soil’s conditions on the embankment’s fragility. To achieve this, the response of three highway embankments resting on sandy soil was examined through quasi-static parametric numerical analyses. For the establishment of fragility curves, a cumulative lognormal probability distribution function was used. The maximum vertical displacement of the embankments’ external surface and the fault displacement were considered as the damage indicator and the intensity measure, respectively. Damage levels were categorized into three qualitative thresholds: minor, moderate, and extensive. All fragility curves were generated for normal and reverse faults, as well as the combination of those fault types (dip-slip fault). Finally, the proposed curves were verified via their comparison with those provided by HAZUS. It was concluded that embankment geometry and depth of fault rupture appearance do not significantly affect fragility, as exceedance probabilities show minimal differences (<4%). However, an embankment founded on dense sandy soil reveals slightly higher fragility compared to the one founded on loose sand. Differences regarding the probability of exceedance of a certain damage level are restricted by a maximum of 7%.

Evaluating Meaningful Changes in Patient-Reported Outcome Measurement Information System-Fatigue Scores from Three Phase 3 Clinical Trials of Sarilumab for Patients With Rheumatoid Arthritis.

The aim of this study was to evaluate changes in fatigue measured by Patient-Reported Outcome Measurement Information System (PROMIS)-Fatigue scores in patients with rheumatoid arthritis (RA) who received sarilumab and to assess the proportion of patients achieving clinically meaningful change. Data from three phase 3 randomized controlled trials of patients with RA who received sarilumab-MOBILITY, TARGET, and MONARCH-were evaluated. The 10 RA-relevant items from the 13-item Functional Assessment of Chronic Illness Therapy (FACIT)-Fatigue were scored in the PROMIS T score metric. Mean changes in 10-item PROMIS-Fatigue T score (PROMIS-Fatigue 10a) were compared, proportions of patients reporting meaningful within-person change thresholds were assessed, and results were visualized using empirical cumulative distribution function (eCDF) curves. Patients with RA reported high baseline fatigue. Using PROMIS-Fatigue 10a, at week 24, patients receiving 150 or 200 mg sarilumab every other week in MOBILITY and TARGET had rapidly and significantly improved mean levels of fatigue compared to those who received placebo. When compared to patients who received adalimumab in MONARCH, patients who received sarilumab had a trend toward increased improvement. eCDF curves showed separation between active treatment versus placebo with both sarilumab doses and across the score range for improvement. Higher proportions of patients reported three-, five-, and seven-point improvements in PROMIS-Fatigue scores in groups who received active treatment. Substantial proportions of patients with RA who received sarilumab reported meaningful change in fatigue measured by PROMIS-Fatigue 10a over time. This study demonstrates the ability to convert FACIT-Fatigue score onto the PROMIS T score metric, the rapid reduction in fatigue with biologic therapies, and the use of novel eCDF curves to show individual patient-level change.

Identifying thresholds for meaningful improvements in NTDT-PRO scores to support conclusions about treatment benefit in clinical studies of patients with non-transfusion-dependent beta-thalassaemia: analysis of pooled data from a phase 2, double-blind, placebo-controlled, randomised trial

ObjectivesTo estimate thresholds for defining meaningful within-patient improvement from baseline to weeks 13–24 and interpreting meaningfulness of between-group difference for the non-transfusion-dependent beta-thalassaemia patient-reported outcome (NTDT-PRO) tiredness/weakness (T/W) and shortness...

DUS Topp–Leone-G Family of Distributions: Baseline Extension, Properties, Estimation, Simulation and Useful Applications

This study introduces the DUS Topp–Leone family of distributions, a novel extension of the Topp–Leone distribution enhanced by the DUS transformer. We derive the cumulative distribution function (CDF) and probability density function (PDF), demonstrating the distribution’s flexibility in modeling various lifetime phenomena. The DUS-TL exponential distribution was studied as a sub-model, with analytical and graphical evidence revealing that it exhibits a unique unimodal shape, along with fat-tail characteristics, making it suitable for time-to-event data analysis. We evaluate parameter estimation methods, revealing that non-Bayesian approaches, particularly Maximum Likelihood and Least Squares, outperform Bayesian techniques in terms of bias and root mean square error. Additionally, the distribution effectively models datasets with varying skewness and kurtosis values, as illustrated by its application to total factor productivity data across African countries and the mortality rate of people who injected drugs. Overall, the DUS Topp–Leone family represents a significant advancement in statistical modeling, offering robust tools for researchers in diverse fields.

Skew-Symmetric Generalized Normal and Generalized t Distributions

In this paper, we introduce the skew-symmetric generalized normal and the skew-symmetric generalized t distributions, which are skewed extensions of symmetric special cases of generalized skew-normal and generalized skew-t distributions, respectively. We derive key distributional properties for these new distributions, including a recurrence relation and an explicit form for the cumulative distribution function (cdf) of the skew-symmetric generalized t distribution. Numerical examples including a simulation study and a real data analysis are presented to illustrate the practical applicability of these distributions.

Global, regional, and national lifetime risk of developing and dying from lung cancer in 2022: A population-based study in 185 countries

Abstract Background: Lifetime cancer risk is an index that indicates the cumulative probability of cancer at some age during a person’s lifetime. Nevertheless, comparative evaluations regarding the probability of developing lung cancer and dying from the disease among diverse populations at the global, regional, and national levels are scarce. Methods: Lung cancer data from 185 countries were obtained from GLOBOCAN 2022, and data on any other cause of death were acquired from the United Nations. The lifetime risks of lung cancer development and death were estimated using adjustment for multiple primary cancers (AMP) method. The lung cancer risks in countries or regions worldwide were compared by region and the Human Development Index (HDI). Results: The global lifetime risk of developing and dying from lung cancer in 2022 was 3.49% and 2.69%, respectively. The lifetime probabilities of developing lung cancer in countries/areas with low, medium, high, and very high HDIs were 0.33%, 0.95%, 4.72%, and 5.29%, and dying from lung cancer in low, medium, high and very high HDI countries were 0.30%, 0.86%, 3.69% and 3.92%, respectively. After the age of 40 years, the remaining probability of lung cancer development and death decreased with age, leaving a residual risk of 2.00% and 1.71%, respectively, starting at 70 years. Conclusions: The probability of developing lung cancer during one’s lifetime is equivalent to 1 in 28 and 1 in 37 people suffering and dying from lung cancer. The age-related risk of developing and dying of lung cancer varies among geographic locations with different HDIs.

Bivariate Generalized Exponential Distribution with Positive Probability at (X = 0, Y = 0) and Estimation of Parameters for a Particular Case

Kundu and Gupta, 2009, J Multivar Anal, 100, 581–593, provided a bivariate generalized exponential distribution (BVGED [Formula: see text]), which is a bivariate continuous lifetime distribution. In practice, however, sometimes both the components may fail instantaneously. Thus, we get a mixture bivariate distribution with positive probability at instantaneous failure of each component. The main aim of this article is to define a BVGED with positive probability at instantaneous failure of each component (BVGEDP [Formula: see text]), where PX=0P(X = 0) and P(Y = 0) is a function of parameter [Formula: see text]. It is observed that the joint probability density function and the cumulative distribution function can be expressed in compact forms. Several properties of the distribution have been discussed. For a particular case (BVGEDP ([Formula: see text] 1, 1, 1)), moment type estimators are obtained which are in closed form and maximum likelihood estimators of parameters ([Formula: see text]) are obtained using an iterative procedure. Also, their finite sample and asymptotic properties are discussed using simulation. A final section presents an application to a real data set on which the proposed BVGEDP ([Formula: see text], 1, 1, 1) distribution is fitted. AMS Subject Classification: 62E99

Gumbel–Logistic Unit Distribution with Application in Telecommunications Data Modeling

The manuscript deals with a new unit distribution that depends on two positive parameters. The distribution itself was obtained from the Gumbel distribution, i.e., by its transformation, using generalized logistic mapping, into a unit interval. In this way, the so-called Gumbel-logistic unit (abbr. GLU) distribution is obtained, and its key properties, such as cumulative distribution function, modality, hazard and quantile function, moment-based characteristics, Bayesian inferences and entropy, have been investigated in detail. Among others, it is shown that the GLU distribution, unlike the Gumbel one which is always positively asymmetric, can take both asymmetric forms. An estimation of the parameters of the GLU distribution, based on its quantiles, is also performed, together with asymptotic properties of the estimates thus obtained and their numerical simulation. Finally, the GLU distribution has been applied in modeling the empirical distributions of some real-world data related to telecommunications.

Application of a Reservoir Classification Method Based on Core Data from Offshore Tight Reservoirs: A Case Study of the Liushagang Formation in the Beibu Basin

Several methods are currently used to test offshore tight reservoirs. However, the effectiveness of these applications varies among wells, and some exhibit unclear reservoir classifications. These issues lead to difficulties in decision-making during tests and result in higher testing costs. Therefore, to address this issue, this study used reservoirs in the Liushagang Formation of the Beibu Basin as the research object and employed core data to apply the multi-stage FZI method. This method computes the FZI and its cumulative probability, classifying the target reservoir into seven distinct types. According to the Winland R35 method, the target reservoir was classified into five distinct types. Seven characteristic parameters were selected based on the mercury injection experimental data. The K-means clustering method was then used to classify the target reservoirs into two types. The conclusions were that, in this formation, there is predominantly low to extra-low porosity and extra-low to ultra-low permeability. According to relationship models, logged porosity can be used to calculate effective permeability. Combining the multi-stage FZI method with the K-means clustering method for reservoir classification is recommended. This integrated approach facilitates a more comprehensive analysis of the characteristics of offshore low-permeability tight reservoirs at both macro and micro scales after classification. This research provides key insights for enhancing offshore well production.

NIMG-55. DEVELOPING A COMPUTATIONAL PIPELINE TO FORECAST AND SPATIALLY MAP HIGH-GRADE GLIOMA RESPONSE TO RADIOTHERAPY USING BIOPHYSICAL MODELS AND DATA-DRIVEN STATISTICAL ANALYSIS

Abstract High-grade glioma (HGG) presents significant treatment challenges, particularly in identifying less responsive tumor areas to target with adaptive radiotherapy (RT). This study introduces a patient-specific computational pipeline designed to predict and spatially map HGG response to RT, focusing on regions demonstrating resilience to RT. Our computational pipeline is centered around a family of 3D biophysical models describing tumor cell invasion, proliferation, and response to RT which can be personalized for individual patients using longitudinal multiparametric MRI data. Utilizing longitudinal multiparametric MRI data reporting on cell density (diffusion weighted MRI) and the extent of disease (T2-FLAIR and contrast-enhanced T1-weighted MRIs) from 21 patients, ranging from baseline to three weeks into RT, we calibrated a family of biophysical models to forecast tumor cell density up to the final week of RT and one-month follow-up. By employing pareto tail analysis on empirical cumulative distribution function fits of voxel-wise changes in apparent diffusion coefficient maps (ΔADC) between the future images (end of RT, one-month follow-up) and pre-treatment images, we identified areas of increased tumor cellularity on both the ground truth and model predicted cellularity maps. The analysis differentiated tumor voxels into “non-responding” and “responding” categories, based on cutoffs determined through ROC analysis across various conditions—including assessments of both enhancing and non-enhancing tumor regions at different time points. Optimal ΔADC cutoffs for predicted and measured data were established, leading to high area under curve (AUC; ranging from 0.803 to 0.934) values and significant Youden’s index scores (ranging from 0.526 to 0.765) across all conditions. Our findings demonstrate the feasibility of this novel pipeline in delineating biologically relevant RT targets, offering a potential tool for enhancing the efficacy of adaptive RT strategies in treating HGG.

Sojourns of locally self-similar Gaussian processes

The cumulative Parisian ruin probability over a finite time interval [ 0 , T ] for a Gaussian risk process R ( t ) = u + c ( t ) − X ( t ) , t ≥ 0 , is the probability that the total time the process R ( t ) spends below zero during this interval exceeds a threshold L ≥ 0 . In this contribution we derive exact asymptotic approximations of the cumulative Parisian ruin probability for a general class of Gaussian processes introduced in D ȩ bicki and Tabiś [Pickands-Piterbarg constants for self-similar Gaussian processes, Probab. Math. Statist. 40 (2020), pp. 297–315. MR 4206416] assuming that X is locally self-similar. We illustrate our findings with several examples. As a byproduct we show that Berman's constants can be defined alternatively by a self-similar Gaussian process which could be quite different to the fractional Brownian motion.

Microstructural characterization of DEM-based random packings of monodisperse and polydisperse non-convex particles.

Understanding of hard particles in morphologies and sizes on microstructures of particle random packings is of significance to evaluate physical and mechanical properties of many discrete media, such as granular materials, colloids, porous ceramics, active cells, and concrete. The majority of previous lines of research mainly dedicated microstructure analysis of convex particles, such as spheres, ellipsoids, spherocylinders, cylinders, and convex-polyhedra, whereas little is known about non-convex particles that are more close to practical discrete objects in nature. In this study, the non-convex morphology of a three-dimensional particle is devised by using a mathematical-controllable parameterized method, which contains two construction modes, namely, the uniformly distributed contraction centers and the randomly distributed contraction centers. Accordingly, three shape parameters are conceived to regulate the particle geometrical morphology from a perfect sphere to arbitrary non-convexities. Random packing models of hard non-convex particles with mono-/poly-dispersity in sizes are then established using the discrete element modeling Diverse microstructural indicators are utilized to characterize configurations of non-convex particle random packings. The compactness of non-convex particles in packings is characterized by the random close packing fraction fd and the corresponding average coordination number Z. In addition, four statistical descriptors, encompassing the radial distribution function g(r), two-point probability function S2(i)(r), lineal-path function L(i)(r), and cumulative pore size distribution function F(δ), are exploited to demonstrate the high-order microstructure information of non-convex particle random packings. The results demonstrate that the particle shape and size distribution have significant effects on Z and fd; the construction mode of the randomly distributed contraction centers can yield higher fd than that of the uniformly distributed contraction centers, in which the upper limit of fd approaches to 0.632 for monodisperse sphere packings. Moreover, non-convex particles of sizes following the famous Fuller distribution of the power-law distribution of the exponent q = 2.5, have the highest fd (≈0.761) with respect to other q. In contrast, the particle shapes have an almost negligible effect on the four statistical descriptors, but they are remarkably sensitive to particle packing fraction fp and size distribution. The results can provide sound guidance for custom-design of granular media by tailoring specific microstructures of particles.

A New Bivariate Survival Model: The Marshall-Olkin Bivariate Exponentiated Lomax Distribution with Modeling Bivariate Football Scoring Data

This paper focuses on applying the Marshall-Olkin approach to generate a new bivariate distribution. The distribution is called the bivariate exponentiated Lomax distribution, and its marginal distribution is the exponentiated Lomax distribution. Numerous attributes are examined, including the joint reliability and hazard functions, the bivariate probability density function, and its marginals. The joint probability density function and joint cumulative distribution function can be stated analytically. Different contour plots of the joint probability density function and joint reliability and hazard rate functions of the bivariate exponentiated Lomax distribution are given. The unknown parameters and reliability and hazard rate functions of the bivariate exponentiated Lomax distribution are estimated using the maximum likelihood method. Also, the Bayesian technique is applied to derive the Bayes estimators and reliability and hazard rate functions of the bivariate exponentiated Lomax distribution. In addition, maximum likelihood and Bayesian two-sample prediction are considered to predict a future observation from a future sample of the bivariate exponentiated Lomax distribution. A simulation study is presented to investigate the theoretical findings derived in this paper and to evaluate the performance of the maximum likelihood and Bayes estimates and predictors. Furthermore, the real data set used in this paper comprises the scoring times from 42 American Football League matches that took place over three consecutive independent weekends in 1986. The results of utilizing the real data set approve the practicality and flexibility of the bivariate exponentiated Lomax distribution in real-world situations, and the bivariate exponentiated Lomax distribution is suitable for modeling this bivariate data set.

Efficacy of lasmiditan, rimegepant and ubrogepant for acute treatment of migraine in triptan insufficient responders: systematic review and network meta-analysis

BackgroundNovel abortive treatments for migraine, ditans and gepants, have promising implications in triptan-insufficient responders with minimal existing comparative data. Our study aims to synthesize evidence through a systematic review and network meta-analysis to assess the comparative efficacy of lasmiditan, rimegepant and ubrogepant in triptan-insufficient responders.MethodWe searched PubMed, Embase, CENTRAL, and EBSCO Open Dissertations up to May 2024. We included randomized controlled trials (RCTs) that compared novel abortive treatments, including lasmiditan, rimegepant, and ubrogepant, in migraine patients who self-reported insufficient response to triptans. Outcomes are represented using relative risks with corresponding 95% confidence intervals (CI). The surface under the cumulative ranking curve (SUCRA) was used to rank each medication.ResultsA total of five phase 3 RCTs involving 3,004 patients were included in the analysis. All three agents were significantly superior to placebo for two-hour pain freedom (RR = 1.93, 95% CI [1.52, 2.46]), freedom from the most bothersome symptoms at two hours (RR = 1.55, 95% CI [1.37, 1.75]), and pain relief at two hours (RR = 1.46, 95% CI [1.35, 1.58]). No statistically significant differences in efficacy outcomes were observed among the three agents. However, lasmiditan 200 mg had the highest cumulative probability for two-hour pain freedom and relief (SUCRA 0.9, 0.8, respective), while rimegepant led in relieving the most bothersome symptoms (SUCRA 0.7).ConclusionLasmiditan, rimegepant, and ubrogepant are effective for acute treatment of migraine in triptan-insufficient responders, with high-dose lasmiditan showing the highest efficacy for pain control.

Non-liver malignancies as main cause of mortality after HCV eradication among people living with HIV.

In people living with HIV (PLWH) with HCV infection, liver and non-liver-related mortality significantly decreased after receiving direct acting antivirals (DAAs). We aimed to assess main causes and predictors of mortality after sustained virological response (SVR) induced by DAAs. Retrospective study in antiretroviral treatment-experienced PLWH with HCV infection, followed at San Raffaele Hospital, Milan, Italy, who achieved SVR after DAAs. Kaplan-Meier analysis and log-rank test were used to estimate cumulative probability of death for any cause. Cox proportional hazards model was used to estimate adjusted hazard ratio (aHR) of death and the corresponding 95% confidence interval (95%CI); Baseline variables included in the model were: age, diabetes, hepatocellular carcinoma (HCC), α-fetoprotein (AFP), ALBI grade. Among 663 people included with a median follow-up of 4.4 years (IQR=3.5-5.5), 49 died. Overall 5-year cumulative probability of death was 8.0% (95%CI=5.5%-10.4%); 63.2% (n=31/49) died from non-liver-related events [mainly non-liver malignancies (18/49) and cardiovascular events (7/49)].-. At multivariate analysis, death was more likely in older people [aHR (adjusted Hazard Ratio) (5-year older)=1.46, 95%CI=1.16-1.83, p=0.0009], and in people with diabetes [aHR=2.98, 95%CI=1.55-5.71, p=0.001], ALBI grade ≥2 [aHR=2.13, 95%CI=1.17-3.90, p=0.014] and AFP ≥3.4 ng/mL [aHR=1.96, 95%CI=1.01; 3.84, p=0.049]. In our cohort, non-liver-related events and malignancies were the most common cause of death after HCV eradication. Diabetes, ALBI grade ≥2 and AFP≥ 3.4 ng/L were associated with higher risk of death. In PLWH after HCV eradication, regardless of liver disease stage, surveillance of non-liver events, particularly malignancies, should be recommended.

Outcomes Associated With Stereotactic Radiosurgery After Multiple Resections of Nonfunctioning Pituitary Macroadenomas: An International, Multicenter Case Series.

Stereotactic radiosurgery (SRS) represents an effective treatment for nonfunctioning pituitary adenomas (NFPAs). However, no data have yet been published regarding results of SRS on NFPAs after multiple previous resections. Retrospective multicentric data of patients diagnosed with NFPA and who underwent multiple resections (≥2) before SRS were reviewed and analyzed. The treatment interval spanned the period of 1992 to 2022. Cox regression and Kaplan-Meier curves were used to assess predictive factors and the probability of tumor control and hypopituitarism. Among the 311 patients (median age: 50.2 [IQR: 18.0] years), 226 (72.7%) had undergone ≥2 previous resections. The median margin dose was 14 Gy (IQR: 4.0 Gy), and the median tumor volume 3.6 cm3 (IQR: 4.8). Overall, the probability of tumor control after SRS was 93.3% (CI 95%: 89.9-96.9) and 86.7% (CI 95%: 81.1-92.6) at 5 and 10 years, respectively. A margin dose >14 Gy was associated with a decreased risk of tumor progression (hazard ratio = 0.33, CI 95% = 0.15-0.75, P = .008). At a last clinical follow-up of 4.1 (IQR 6.1) years, 10.1% (30/296) developed at least 1 new hormone deficiency after SRS. The cumulative probability of new hormone deficiency was 6.1% (95% CI: 3.0-9.1), 10.3% (95% CI: 5.8-14.6), and 18.9% (95% CI: 11.5-25.8) at 3, 5, and 10 years after SRS, respectively. The average latency between SRS and development of new hormone deficiencies was 3.3 years (IQR 4.1). A maximum point dose to the pituitary stalk >10 Gy was associated with a new deficiency (hazard ratio = 4.06, CI 95% = 1.57-10.5, P-value = .004). For patients with NFPA with multiple previous resections, SRS offers effective local tumor control and a low risk of delayed hypopituitarism for managing these challenging adenomas. SRS should be strongly considered in patients with NFPA with 2 previous resections compared with considering a third resection.

Second Events After Curative-Intent Treatment for Lip Cancer: Navigating the Path of Follow-Up Care.

We aimed to investigate the pattern, risk, and treatment of subsequent events after curative-intent treatment of lip cancer. This retrospective cohort study included 313 patients treated for lip cancer from 2011 to 2021 in a tertiary oncological center. After a median follow-up time of 29.16 months, 145 (46.32%) patients presented with second primary tumors, 93% of which were skin carcinomas. Locoregional recurrence occurred in 7.9% of cases, with 2.5% with nodal recurrence. The 1-, 5-, and 10-year cumulative second primary tumor probabilities were 32.8%, 60.92%, and 70.92%, respectively. A higher risk was observed in elderly patients and basal cell carcinoma cases located on the cutaneous surface of the upper lip. Regional metastasis but not second primary tumors negatively impacted survival. Our study helps fill a literature gap, structuring specific recommendations regarding evaluations and follow-up protocols for patients with lip cancer. Since cutaneous second primary tumors were the most common second event, standard skin examination is key. Age and histology were significant predictors for second primary tumors. For cases of locally advanced lip squamous cell carcinoma, standard guidelines for head and neck cancer must be followed.