Variations in surgical practice and short-term outcomes for degenerative lumbar scoliosis and spondylolisthesis: do surgeon training and experience matter?

For diverse procedures, sizable geographic variation exists in rates and outcomes of surgery, including for degenerative lumbar spine conditions. Little is known about how surgeon training and experience are associated with surgeon-level variations in spine surgery practice and short-term outcomes. This retrospective observational analysis characterized variations in surgical operations for degenerative lumbar scoliosis or spondylolisthesis, two common age-related conditions. The study setting was two large spine surgery centers in one region during 2017-19. Using data (International Classification of Diseases-10th edition and current procedural terminology codes) extracted from electronic health record systems, we characterized surgeon-level variations in practice (use of instrumented fusion - a more extensive procedure that involves device-related risks) and short-term postoperative outcomes (major in-hospital complications and readmissions). Next, we tested for associations between surgeon training (specialty and spine fellowship) and experience (career stage and operative volume) and use of instrumented fusion as well as outcomes. Eighty-nine surgeons performed 2481 eligible operations. For the study diagnoses, spine surgeons exhibited substantial variation in operative volume, use of instrumented fusion, and postoperative outcomes. Among surgeons above the median operative volume, use of instrumented fusion ranged from 0% to >90% for scoliosis and 9% to 100% for spondylolisthesis, while rates of major in-hospital complications ranged from 0% to 25% for scoliosis and from 0% to 14% for spondylolisthesis. For scoliosis, orthopedic surgeons were more likely than neurosurgeons to perform instrumented fusion for scoliosis [49% vs. 33%, odds ratio (OR) = 2.3, 95% confidence interval (95% CI) 1.3-4.2, P-value = .006] as were fellowship-trained surgeons (49% vs. 25%, OR = 3.0, 95% CI 1.6-5.8; P = .001). Fellowship-trained surgeons had lower readmission rates. Surgeons with higher operative volumes used instrumented fusion more often (OR = 1.1, 95% CI 1.0-1.2, P < .05 for both diagnoses) and had lower rates of major in-hospital complications (OR = 0.91, 95% CI 0.85-0.97; P = .006). Surgical practice can vary greatly for degenerative spine conditions, even within the same region and among colleagues at the same institution. Surgical specialty and subspecialty, in addition to recent operative volume, can be linked to variations in spine surgeons' practice patterns and outcomes. These findings reinforce the notion that residency and fellowship training may contribute to variation and present important opportunities to optimize surgical practice over the course of surgeons' careers. Future efforts to reduce unexplained variation in surgical practice could test interventions focused on graduate medical education. Graphical Abstract.

Dynamic Risk Prediction of Treatment Discontinuation Using Patient-Reported Outcomes Data in the Phase III NSABP B-35 Trial.

Predicting an individual's risk of treatment discontinuation is critical for the implementation of precision chemoprevention. We developed partly conditional survival models to predict discontinuation of tamoxifen or anastrozole using patient-reported outcome (PRO) data from postmenopausal women with ductal carcinoma in situ enrolled in the NSABP B-35 clinical trial. In a secondary analysis of the NSABP B-35 clinical trial PRO data, we proposed two models for treatment discontinuation within each treatment arm (anastrozole or tamoxifen treated patients) using partly conditional Cox-type models with time-dependent covariates. A 70/30 split of the sample was used for the training and validation datasets. The predictive performance of the models was evaluated using calibration and discrimination measures based on the Brier score and AUC from time-dependent ROC curves. The predictive models stratified high-risk versus low-risk early discontinuation at a 6-month horizon. For anastrozole-treated patients, predictive factors included baseline body mass index (BMI) and longitudinal patient-reported symptoms such as insomnia, joint pain, hot flashes, headaches, gynecologic symptoms, and vaginal discharge, all collected up to 12 months [Brier score, 0.039; AUC, 0.76; 95% confidence interval (CI), 0.57-0.95]. As for tamoxifen-treated patients, predictive factors included baseline BMI, and time-dependent covariates: cognitive problems, feelings of happiness, calmness, weight problems, and pain (Brier score, 0.032; AUC, 0.78; 95% CI, 0.65-0.91). A real-time calculator based on these models was developed in Shiny to create a web-based application with a future goal to aid healthcare professionals in decision-making. PREVENTION RELEVANCE: The dynamic prediction provided by partly conditional models offers valuable insights into the treatment discontinuation risks using PRO data collected over time from clinical trial participants. This tool may benefit healthcare professionals in identifying patients at high risk of premature treatment discontinuation and support interventions to prevent potential discontinuation.

Does the Addition of Mutations of CTNNB1 S45F to Clinical Factors Allow Prediction of Local Recurrence in Patients With a Desmoid Tumor? A Local Recurrence Risk Model.

BACKGROUND: The initial approach to the treatment of desmoid tumors has changed from surgical resection to watchful waiting. However, surgery is still sometimes considered for some patients, and it is likely that a few patients would benefit from tumor removal if the likelihood of local recurrence could be predicted. However, to our knowledge, there is no tool that can provide guidance on this for clinicians at the point of care. QUESTION/PURPOSE: We sought to explore whether a combined molecular and clinical prognostic model for relapse in patients with desmoid tumors treated with surgery would allow us to identify patients who might do well with surgical excision. METHODS: This was a retrospective, single-center study of 107 patients with desmoid tumors who were surgically treated between January 1980 and December 2015, with a median follow-up of 106 months (range 7 to 337 months). We correlated clinical variables (age, tumor size, and localization) and CTNNB1 gene mutations with recurrence-free survival. Recurrence-free survival was estimated using a Kaplan-Meier curve. Univariate and multivariable analyses of time to local recurrence were performed using Cox regression models. A final nomogram model was constructed according to the final fitted Cox model. The predictive performance of the model was evaluated using measures of calibration and discrimination: calibration plot and the Harrell C-statistic, also known as the concordance index, in which values near 0.5 represent a random prediction and values near 1 represent the best model predictions. RESULTS: The multivariable analysis showed that S45F mutations (hazard ratio 5.25 [95% confidence interval 2.27 to 12.15]; p < 0.001) and tumor in the extremities (HR 3.15 [95% CI 1.35 to 7.33]; p = 0.008) were associated with a higher risk of local recurrence. Based on these risk factors, we created a model; we observed that patients considered to be at high risk of local recurrence as defined by having one or two factors associated with recurrence (extremity tumors and S45F mutation) had an HR of 8.4 compared with patients who had no such factors (95% CI 2.84 to 24.6; p < 0.001). From these data and based on the multivariable Cox models, we also developed a nomogram to estimate the individual risk of relapse after surgical resection. The model had a concordance index of 0.75, or moderate discrimination. CONCLUSION: CTNNB1 S45F mutations combined with other clinical variables are a potential prognostic biomarker associated with the risk of relapse in patients with desmoid tumors. The developed nomogram is simple to use and, if validated, could be incorporated into clinical practice to identify patients at high risk of relapse among patients opting for surgical excision and thus help clinicians and patients in decision-making. A large multicenter study is necessary to validate our model and explore its applicability. LEVEL OF EVIDENCE: Level III, therapeutic study.

Systemic immune mediators reflect tumour-infiltrating lymphocyte intensity and predict therapeutic response in triple-negative breast cancer.

Triple-negative breast cancer (TNBC) is an aggressive form of breast cancer (BC). Neoadjuvant chemotherapy has proven efficacy in its treatment, and a pathological complete response (pCR) to therapy is predictive of improved long-term survival. The immune response is key to successful neoadjuvant chemotherapy, as indicated by the relation between the percentage of stromal tumour-infiltrating lymphocytes (TILs) in pre-treated tumour tissue samples and the likelihood of achieving pCR. Here we studied systemic immune mediators from volunteer TNBC patients before undergoing neoadjuvant chemotherapy to determine the systemic response association with TIL intensity, treatment response and survival. Patients were classified into pCR responder or non-responder at time of surgery. We found higher levels of immune mediators before treatment began in patients that went on to be pCR responders versus non-pCR, with area under the curve (AUC) values of 0.64-0.80. We also observed a positive correlation between inflammatory systemic immune mediators and the percentage of TILs in pCR responder patients. Combining TILs and systemic immune mediator levels provided stronger AUC values (range of 0.72-0.82). Last, performing a progression-free survival analysis with several of the systemic cytokines that predict pCR, segregated the patients into long- and short-survival groups based on high and low production of the cytokines, respectively. Our study demonstrates that circulating cytokines, before treatment begins, predict pCR in TNBC patients treated with neoadjuvant chemotherapy. Moreover, they may act as a surrogate marker of high TILs or together with TILs to better predict pCR and survival.

A general class of promotion time cure rate models with a new biological interpretation.

Over the last decades, the challenges in survival models have been changing considerably and full probabilistic modeling is crucial in many medical applications. Motivated from a new biological interpretation of cancer metastasis, we introduce a general method for obtaining more flexible cure rate models. The proposal model extended the promotion time cure rate model. Furthermore, it includes several well-known models as special cases and defines many new special models. We derive several properties of the hazard function for the proposed model and establish mathematical relationships with the promotion time cure rate model. We consider a frequentist approach to perform inferences, and the maximum likelihood method is employed to estimate the model parameters. Simulation studies are conducted to evaluate its performance with a discussion of the obtained results. A real dataset from population-based study of incident cases of melanoma diagnosed in the state of São Paulo, Brazil, is discussed in detail.

Endoscopic assessment of radiological stage IVA cervical cancer: A bivariate meta-analysis supporting an evidence-based staging algorithm proposal.

OBJECTIVE: To optimize the use of confirmatory endoscopic exams (cystoscopy/proctoscopy) in the staging of locally advanced cervical cancer (LACC), the present study evaluates the predictive value of radiological exams (CT and MRI) to detect bladder/rectum invasion. METHODS: A systematic search of databases (PubMed and EMBASE) was performed (CRD42021270329). The inclusion criteria were: a) cervix cancer diagnosis; b) staging CT and/or MRI (index test); c) staging cystoscopy and/or proctoscopy (standard test); and d) numbers of true positives (TP), true negatives (TN), false positives (FP), and false negatives (FN) provided. A random-effects bivariate meta-analysis of positive predictive value (PPV) and negative predictive value (NPV) was performed with moderator analyses by imaging modality (CT and MRI) and prevalence. RESULTS: Nineteen studies met the inclusion criteria, totaling 3480 and 1641 patients for bladder and rectum analyses, respectively. For bladder invasion (prevalence ranged from 0.9% to 34.5%), the overall PPV was 45% (95% confidence interval, 33%-57%, based on 19 studies). Per subgroup, the PPV was 31% for MRI/prevalence ≤6%, 33% for CT/prevalence ≤6%, and 69% for CT/prevalence >6%. For rectal invasion (prevalence ranged from 0.4% to 20.0%), the overall PPV was 30% (95% confidence interval, 17%-47%, based on 8 studies). Per subgroup, the PPV was 36% for MRI/prevalence ≤1%, 17% for MRI/prevalence >1%, and 38% for CT/prevalence >1%. The overall NPV for bladder invasion and rectal invasion were 98% (95% confidence interval, 97%-99%) and 100% (95% confidence interval, 99%-100%), respectively. Considering prevalence and radiological modality, the point estimate of NPV varied from 95% to 100% for bladder invasion and from 99% to 100% for rectum invasion. CONCLUSIONS: Due to low PPV (<50%) of radiological staging, endoscopic exams may be necessary to correctly assess radiological stage IVA LACC. However, they are not necessary after negative radiological exam (NPV ≥95%).

Nonproportional hazards model with a frailty term for modeling subgroups with evidence of long-term survivors: Application to a lung cancer dataset.

With advancements in medical treatments for cancer, an increase in the life expectancy of patients undergoing new treatments is expected. Consequently, the field of statistics has evolved to present increasingly flexible models to explain such results better. In this paper, we present a lung cancer dataset with some covariates that exhibit nonproportional hazards (NPHs). Besides, the presence of long-term survivors is observed in subgroups. The proposed modeling is based on the generalized time-dependent logistic model with each subgroup's effect time and a random term effect (frailty). In practice, essential covariates are not observed for several reasons. In this context, frailty models are useful in modeling to quantify the amount of unobservable heterogeneity. The frailty distribution adopted was the weighted Lindley distribution, which has several interesting properties, such as the Laplace transform function on closed form, flexibility in the probability density function, among others. The proposed model allows for NPHs and long-term survivors in subgroups. Parameter estimation was performed using the maximum likelihood method, and Monte Carlo simulation studies were conducted to evaluate the estimators' performance. We exemplify this model's use by applying data of patients diagnosed with lung cancer in the state of São Paulo, Brazil.

Circulating Angiogenic Factor Levels in Hypertensive Disorders of Pregnancy.

BACKGROUND: Among women with hypertensive disorders of pregnancy, biomarkers may stratify risk for developing preeclampsia with severe features (sPE). METHODS: Across 18 U.S. centers, we prospectively measured the ratio of serum soluble fms-like tyrosine kinase 1 (sFlt-1) to placental growth factor (PlGF) in pregnant women hospitalized between 23 and 35 weeks of gestation. The primary outcome was predicting sPE, and secondary outcomes included predicting adverse outcomes within 2 weeks. The prognostic performance of the sFlt-1:PlGF ratio was assessed by using a derivation/validation design. RESULTS: A total of 1014 pregnant women were evaluated; 299 were included in the derivation cohort and 715 in the validation cohort. In the derivation cohort, the median sFlt-1:PlGF ratio was 200 (interquartile range, 53 to 458) among women who developed sPE compared with 6 (interquartile range, 3 to 26) in those who did not (P<0.001). The discriminatory ratio of ≥40 was then tested in the validation cohort and yielded a 65% positive (95% confidence interval [CI], 59 to 71) and a 96% negative (95% CI, 93 to 98) predictive value for the primary outcome. The ratio performed better than standard clinical measures (area under the receiver-operating characteristic curve, 0.92 versus <0.75 for standard-of-care tests). Compared with women with a ratio <40, women with a ratio ≥40 were at higher risk for adverse maternal outcomes (16.1% versus 2.8%; relative risk, 5.8; 95% CI, 2.8 to 12.2). CONCLUSIONS: In women with a hypertensive disorder of pregnancy presenting between 23 and 35 weeks of gestation, measurement of serum sFlt-1:PlGF provided stratification of the risk of progressing to sPE within the coming fortnight. (Funded by Cedars-Sinai Medical Center and Thermo Fisher Scientific; ClinicalTrials.gov NCT03815110.)

On a new piecewise regression model with cure rate: Diagnostics and application to medical data.

In this article, we discuss an extension of the classical negative binomial cure rate model with piecewise exponential distribution of the time to event for concurrent causes, which enables the modeling of monotonic and non-monotonic hazard functions (ie, the shape of the hazard function is not assumed as in traditional parametric models). This approach produces a flexible cure rate model, depending on the choice of time partition. We discuss local influence on this negative binomial power piecewise exponential model. We report on Monte Carlo simulation studies and application of the model to real melanoma and leukemia datasets.

Weighted Lindley frailty model: estimation and application to lung cancer data.

In this paper, we propose a novel frailty model for modeling unobserved heterogeneity present in survival data. Our model is derived by using a weighted Lindley distribution as the frailty distribution. The respective frailty distribution has a simple Laplace transform function which is useful to obtain marginal survival and hazard functions. We assume hazard functions of the Weibull and Gompertz distributions as the baseline hazard functions. A classical inference procedure based on the maximum likelihood method is presented. Extensive simulation studies are further performed to verify the behavior of maximum likelihood estimators under different proportions of right-censoring and to assess the performance of the likelihood ratio test to detect unobserved heterogeneity in different sample sizes. Finally, to demonstrate the applicability of the proposed model, we use it to analyze a medical dataset from a population-based study of incident cases of lung cancer diagnosed in the state of São Paulo, Brazil.

Survival models induced by zero-modified power series discrete frailty: Application with a melanoma data set.

Survival models with a frailty term are presented as an extension of Cox's proportional hazard model, in which a random effect is introduced in the hazard function in a multiplicative form with the aim of modeling the unobserved heterogeneity in the population. Candidates for the frailty distribution are assumed to be continuous and non-negative. However, this assumption may not be true in some situations. In this paper, we consider a discretely distributed frailty model that allows units with zero frailty, that is, it can be interpreted as having long-term survivors. We propose a new discrete frailty-induced survival model with a zero-modified power series family, which can be zero-inflated or zero-deflated depending on the parameter value. Parameter estimation was obtained using the maximum likelihood method, and the performance of the proposed models was performed by Monte Carlo simulation studies. Finally, the applicability of the proposed models was illustrated with a real melanoma cancer data set.

Prognostic value of response evaluation based on breast MRI after neoadjuvant treatment: a retrospective cohort study.

OBJECTIVE: To investigate the impact of response evaluation after neoadjuvant chemotherapy (NAC) in breast cancer patients, assessed by both magnetic resonance imaging (MRI) and pathology, on disease-free survival (DFS). METHODS: This single-center, retrospective cohort study included consecutive breast cancer patients who underwent NAC and preoperative breast MRI. Resolution of invasive carcinoma in the breast and axilla was defined as complete pathological response (pCR). Radiological complete response (rCR) was defined as the absence of abnormal enhancement in the tumor site. Kaplan-Meier estimator was used to estimate the disease-free survival on 60 months. Cox regression analysis was used to estimate hazard ratio (HR) values. RESULTS: In total, 317 patients were included with a mean age of 47.3 years and a mean tumor size of 39.8 mm. The most common immunophenotype was luminal (44.9%), followed by triple-negative (26.8%). Overall, 126 patients (39.7%) had an rCR, while 119 (37.5%) had pCR; the radiological and pathological responses agreed in 252 cases (79.5%). During follow-up, patients who had rCR and pCR had a better DFS curve compared to patients with non-rCR and non-pCR, while those who had rCR or pCR presented an intermediate curve (Log-rank p = 0.003). Multivariate analysis showed a higher risk of recurrence in patients with non-rCR and non-pCR (HR: 5,626; p = 0.020) and those who had a complete response on MRI or pathology only (HR: 4,369; p = 0.067), when compared to patients with rCR and pCR. CONCLUSIONS: The association of MRI and pathological responses after NAC might better stratify the risk of recurrence and prognosis in breast cancer patients. KEY POINTS: • Association of response evaluation after neoadjuvant chemotherapy by pathology and MRI allows better stratification of prognosis. • Complete response to neoadjuvant chemotherapy on pathology and MRI was related to better disease-free survival. • Complete response on MRI or pathology only had a greater risk of recurrence.

Risk of in-hospital death associated with Covid-19 lung consolidations on chest computed tomography - A novel translational approach using a radiation oncology contour software.

PURPOSE: To determine whether the percentage of lung involvement at the initial chest computed tomography (CT) is related to the subsequent risk of in-hospital death in patients with coronavirus disease-2019 (Covid-19). MATERIALS AND METHODS: Using a cohort of 154 laboratory-confirmed Covid-19 pneumonia cases that underwent chest CT between February and April 2020, we performed a volumetric analysis of the lung opacities. The impact of relative lung involvement on outcomes was evaluated using multivariate logistic regression. The primary endpoint was the in-hospital mortality rate. The secondary endpoint was major adverse hospitalization events (intensive care unit admission, use of mechanical ventilation, or death). RESULTS: The median age of the patients was 65 years: 50.6 % were male, and 36.4 % had a history of smoking. The median relative lung involvement was 28.8 % (interquartile range 9.5-50.3). The overall in-hospital mortality rate was 16.2 %. Thirty-six (26.3 %) patients were intubated. After adjusting for significant clinical factors, there was a 3.6 % increase in the chance of in-hospital mortality (OR 1.036; 95 % confidence interval, 1.010-1.063; P = 0.007) and a 2.5 % increase in major adverse hospital events (OR 1.025; 95 % confidence interval, 1.009-1.042; P = 0.002) per percentage unit of lung involvement. Advanced age (P = 0.013), DNR/DNI status at admission (P < 0.001) and smoking (P = 0.008) also increased in-hospital mortality. Older (P = 0.032) and male patients (P = 0.026) had an increased probability of major adverse hospitalization events. CONCLUSIONS: Among patients hospitalized with Covid-19, more lung consolidation on chest CT increases the risk of in-hospital death, independently of confounding clinical factors.

Development and validation of a Brazilian nomogram to assess sentinel node biopsy positivity in melanoma.

BACKGROUND: Although well-established, sentinel node biopsy (SNB) for melanoma is not free from controversies and sometimes it can be questionable if SNB should be considered even for patients who meet the criteria for the procedure. Mathematical tools such as nomograms can be helpful and give more precise answers for both clinicians and patients. We present a nomogram for SNB positivity that has been internally validated. METHODS: Retrospective analysis of patients who underwent SNB from 2000 to 2015 in a single institution. Single logistic regressions were used to identify variables that were associated to SNB positivity. All variables with a p value < 0.05 were included in the final model. Overall performance, calibration, and discriminatory power of the final multiple logistic regression model were all assessed. Internal validation of the multiple logistic regression model was performed via bootstrap analysis based on 1000 replications. RESULTS: Site of primary lesion, Breslow thickness, mitotic rate, histologic regression, lymphatic invasion, and Clark level were statistically related to SNB positivity. After internal validation, a good performance was observed as well as an adequate power of discrimination (area under the curve 0.751). CONCLUSIONS: We have presented a nomogram that can be helpful and easily used in daily practice for assessing SNB positivity.

Multidetector Computed Tomography with Dedicated Protocol for Breast Cancer Locoregional Staging: Feasibility Study.

BACKGROUND: The aim of this study was to demonstrate the feasibility of performing multidetector computed tomography (MDCT) with a dedicated protocol for locoregional staging in breast cancer patients. METHODS: This prospective single-center study included newly diagnosed breast cancer patients submitted to contrast-enhanced chest MDCT and breast magnetic resonance imaging (MRI). MDCT was performed in prone position and using subtraction techniques. Fleiss' Kappa coefficient (K) and intraclass correlation coefficient (ICC) were used to assess agreement between MRI, MDCT, and pathology, when available. RESULTS: Thirty-three patients were included (mean age: 47 years). Breast MRI and MDCT showed at least substantial agreement for evaluation of tumor extension (k = 0.674), presence of multifocality (k = 0.669), multicentricity (k = 0.857), nipple invasion (k = 1.000), skin invasion (k = 0.872), and suspicious level I axillary lymph nodes (k = 0.613). MDCT showed higher number of suspicious axillary lymph nodes than MRI, especially on levels II and III. Both methods had similar correlation with tumor size (MRI ICC: 0.807; p = 0.008 vs. MDCT ICC: 0.750; p = 0.020) and T staging (k = 0.699) on pathology. CONCLUSIONS: MDCT with dedicated breast protocol is feasible and showed substantial agreement with MRI features in stage II or III breast cancer patients. This method could potentially allow one-step locoregional and systemic staging, reducing costs and improving logistics for these patients.

Systematic review and meta-analysis of gemcitabine-based chemotherapy after FOLFIRINOX in advanced pancreatic cancer.

BACKGROUND: There are no randomized data to guide treatment decisions for patients with advanced pancreatic adenocarcinoma following first-line FOLFIRINOX. We performed a systematic review and meta-analysis of studies using gemcitabine-based chemotherapy after FOLFIRINOX to assess treatment efficacy and toxicity. METHODS: We included studies published between 2011 and 2018 that evaluated the efficacy and toxicity of gemcitabine-based chemotherapy after FOLFIRINOX in patients with advanced pancreatic adenocarcinoma. We searched PubMed, Embase, Scopus, and Web of Science. Primary outcomes were objective response rate (ORR), disease control rate (DCR), any grade 3/4 toxicity rate, and progression-free survival (PFS). We used the random-effects model to generate pooled estimates for proportions. RESULTS: Sixteen studies met the eligibility criteria. Overall, ORR was 10.8%, DCR was 41.1%, and any grade 3/4 toxicity rate was 28.6%. In subgroup analyses, gemcitabine plus nab-paclitaxel was associated with superior ORR (14.4 versus 8.4%; p = 0.038) and DCR (53.5 versus 30.5%; p < 0.001) compared with single-agent gemcitabine. Median PFS ranged from 1.9 to 6.4 months and numerically favored gemcitabine plus nab-paclitaxel. CONCLUSIONS: Our study suggests gemcitabine-based chemotherapy likely outperforms best supportive care after FOLFIRINOX in advanced pancreatic cancer. Also, gemcitabine plus nab-paclitaxel seems to be more active than single-agent gemcitabine (CRD42018100421).

Long-term frailty modeling using a non-proportional hazards model: Application with a melanoma dataset.

The semiparametric Cox regression model is often fitted in the modeling of survival data. One of its main advantages is the ease of interpretation, as long as the hazards rates for two individuals do not vary over time. In practice the proportionality assumption of the hazards may not be true in some situations. In addition, in several survival data is common a proportion of units not susceptible to the event of interest, even if, accompanied by a sufficiently large time, which is so-called immune, "cured," or not susceptible to the event of interest. In this context, several cure rate models are available to deal with in the long term. Here, we consider the generalized time-dependent logistic (GTDL) model with a power variance function (PVF) frailty term introduced in the hazard function to control for unobservable heterogeneity in patient populations. It allows for non-proportional hazards, as well as survival data with long-term survivors. Parameter estimation was performed using the maximum likelihood method, and Monte Carlo simulation was conducted to evaluate the performance of the models. Its practice relevance is illustrated in a real medical dataset from a population-based study of incident cases of melanoma diagnosed in the state of São Paulo, Brazil.

Defective regression models for cure rate modeling with interval-censored data.

Regression models in survival analysis are most commonly applied for right-censored survival data. In some situations, the time to the event is not exactly observed, although it is known that the event occurred between two observed times. In practice, the moment of observation is frequently taken as the event occurrence time, and the interval-censored mechanism is ignored. We present a cure rate defective model for interval-censored event-time data. The defective distribution is characterized by a density function whose integration assumes a value less than one when the parameter domain differs from the usual domain. We use the Gompertz and inverse Gaussian defective distributions to model data containing cured elements and estimate parameters using the maximum likelihood estimation procedure. We evaluate the performance of the proposed models using Monte Carlo simulation studies. Practical relevance of the models is illustrated by applying datasets on ovarian cancer recurrence and oral lesions in children after liver transplantation, both of which were derived from studies performed at A.C. Camargo Cancer Center in São Paulo, Brazil.

Genomics and epidemiology for gastric adenocarcinomas (GE4GAC): a Brazilian initiative to study gastric cancer

Gastric cancer (GC) is the fifth most common type of cancer worldwide with high incidences in Asia, Central, and South American countries. This patchy distribution means that GC studies are neglected by large research centers from developed countries. The need for further understanding of this complex disease, including the local importance of epidemiological factors and the rich ancestral admixture found in Brazil, stimulated the implementation of the GE4GAC project. GE4GAC aims to embrace epidemiological, clinical, molecular and microbiological data from Brazilian controls and patients with malignant and pre-malignant gastric disease. In this letter, we summarize the main goals of the project, including subject and sample accrual and current findings

Late assessment of quality of life in patients with rectal carcinoma: comparison between sphincter preservation and definitive colostomy.

PURPOSE: Patients with cancer of the lower and middle rectum who are candidates for curative surgery often have negative opinions on definitive colostomy. The purpose of this study is to compare the quality of life (QoL) of patients who undergo standard treatment for rectal cancer with sphincter preservation or definitive colostomy. METHODS: A total of 125 patients with adenocarcinoma of the lower or middle rectum who underwent radical surgery with curative intent with a follow-up ≥ 1 year were recruited: 83 patients (group 1) were subjected to low anterior resection and low colorectal or coloanal anastomosis-thus preserving their sphincter-and 42 (group 2) were treated with abdominoperineal resection, followed by terminal definitive colostomy. QoL was assessed with the EORTC QLQ-C30 and QLQ-CR29 questionnaires. RESULTS: Health and global quality of life were similar between groups; however, patients who underwent definitive colostomy had higher scores on the emotional (p value = 0.016) and cognitive function scales (p value = 0.017). Patients with sphincter preservation presented with more symptoms that were related to stool frequency (p value < 0.001), intestinal constipation (p value = 0.005), fecal incontinence (p value = 0.001), buttock pain (p value = 0.023), and nausea and vomiting (p value = 0.036), whereas patients with permanent colostomy had higher scores for dysuria (p value = 0.033). CONCLUSION: Although global QoL scores did not differ between groups, patients who underwent definitive colostomy had significantly better functional and symptom scale scores, reflecting greater function with fewer symptoms.