Incidence Function Model Research Articles

Metapopulation models using landscape connectivity can better reflect landscape heterogeneity

Forest fragmentation due to urban development has a significant impact on species persistence, necessitating a metapopulation theory approach considering landscape structure and patch-based impact assessments. In this study, we propose a method that applies landscape connectivity and incidence function models (IFM) to a species distribution model to represent the persistence of metapopulations by considering landscape structure (IFM-LCONS). The proposed approach was used to understand changes in leopard cat (Prionailurus bengalensis) occupancy patterns resulting from urban development considering landscape and patch structure. The impact on changes in occupancy owing to urban development was better reflected by patch area (R2 = 0.5031, R2 = 0.1642) and quality (R2 = 0.5142, R2 = 0.1042). Notably, the IFM-LCONS showed an increasing occupancy at a connectivity value of 500, whereas the IFM indicated the opposite. These results highlight that the here proposed approach allows for a more thorough consideration of the impact of urban development on landscape and structural aspects with respect to endangered and rare species, which can be used for conservation planning.

Competing Risks and Analysis of Patients with Brain Stroke: Cumulative Incidence Function and Cause-Specific Hazard Approach

Introduction: In the presence of competing risks, patients with brain stroke (BS) experience death by various causes, such as diabetes, and heart disease, and other causes in the follow-up. This study aimed to model the survival in patients with BS in the presence of these competing risk of death using cumulative incidence function (CIF) and cause-specific hazard (CSH) models.
 Methods: In the study, 332 patients with the definitive diagnosis of BS were followed up for 10 years, and their mortality status due to BS or other causes was evaluated. In addition, significance tests and parameters were estimated by using STATA 14 software by considering the CIF and CSH model.
 Results: The median follow-up time was 20.68 months for patients who died due to BS and 68.50 months for patients who died due to other causes. In the CIF model, Sex [BS: cumulative incidence hazard ratio (SHR) = 2.35, 90% confidence interval (CI) = (1.76-3.14)], Employment status [BS: 2.04(1.50-2.75)], History of blood pressure[BS: 1.64(1.25-2.14)], Heart disease[BS: 1.47(1.13-1.94)], Cerebrovascular accident type[BS: 0.77(0.69-0.87)]; age [Other case: 59-68 years, 2.61 (1.13-6.06) and ≥76 years: 3.03 (1.32-6.92)] were directly related to hazard of death. The CSH model resulted in similar estimates except for age [BS: 69-75 years; 1.31(1.18-1.45), ≥76 years; 1.37(1.23-1.53); other case: age 59-68 years 1.91 (1.22-2.99) and 69-75 years; 1.89 (1.21-2.96) and ≥76 years: 2.14 (1.36-3.37)], Sex[BS: 1.38(1.07-1.79)], History of blood pressure [BS: 1.57(1.20-2.05)], Heart disease [BS:1.44(1.09-1.91)] were directly related to hazard of death.
 Conclusion: The estimation of CIF analysis, along with CSH one for the competing risks, is suggested to provide more precise information about patients’ status in order to support adopted clinical decisions when aiming at assessing health related to a specific cause economically and determining the probability of occurring an intended event among other causes.

Association of COVID-19 Vaccination With Breakthrough Infections and Complications in Patients With Cancer

Patients with cancer are known to have increased risk of COVID-19 complications, including death. To determine the association of COVID-19 vaccination with breakthrough infections and complications in patients with cancer compared to noncancer controls. Retrospective population-based cohort study using linked administrative databases in Ontario, Canada, in residents 18 years and older who received COVID-19 vaccination. Three matched groups were identified (based on age, sex, type of vaccine, date of vaccine): 1:4 match for patients with hematologic and solid cancer to noncancer controls (hematologic and solid cancers separately analyzed), 1:1 match between patients with hematologic and patients with solid cancer. Cancer diagnosis. Outcomes occurring 14 days after receipt of second COVID-19 vaccination dose: primary outcome was SARS-CoV-2 breakthrough infection; secondary outcomes were emergency department visit, hospitalization, and death within 4 weeks of SARS-CoV-2 infection (end of follow-up March 31, 2022). Multivariable cumulative incidence function models were used to obtain adjusted hazard ratio (aHR) and 95% CIs. A total of 289 400 vaccinated patients with cancer (39 880 hematologic; 249 520 solid) with 1 157 600 matched noncancer controls were identified; the cohort was 65.4% female, and mean (SD) age was 66 (14.0) years. SARS-CoV-2 breakthrough infection was higher in patients with hematologic cancer (aHR, 1.33; 95% CI, 1.20-1.46; P < .001) but not in patients with solid cancer (aHR, 1.00; 95% CI, 0.96-1.05; P = .87). COVID-19 severe outcomes (composite of hospitalization and death) were significantly higher in patients with cancer compared to patients without cancer (aHR, 1.52; 95% CI, 1.42-1.63; P < .001). Risk of severe outcomes was higher among patients with hematologic cancer (aHR, 2.51; 95% CI, 2.21-2.85; P < .001) than patients with solid cancer (aHR, 1.43; 95% CI, 1.24-1.64; P < .001). Patients receiving active treatment had a further heightened risk for COVID-19 severe outcomes, particularly those who received anti-CD20 therapy. Third vaccination dose was associated with lower infection and COVID-19 complications, except for patients receiving anti-CD20 therapy. In this large population-based cohort study, patients with cancer had greater risk of SARS-CoV-2 infection and worse outcomes than patients without cancer, and the risk was highest for patients with hematologic cancer and any patients with cancer receiving active treatment. Triple vaccination was associated with lower risk of poor outcomes.

Statistical Considerations for Analyses of Time-To-Event Endpoints in Oncology Clinical Trials: Illustrations with CAR-T Immunotherapy Studies.

Chimeric antigen receptor T-cell (CAR-T) therapy is an exciting development in the field of cancer immunology and has received a lot of interest in recent years. Many time-to-event (TTE) endpoints related to relapse, disease progression, and remission are analyzed in CAR-T studies to assess treatment efficacy. Definitions of these TTE endpoints are not always consistent, even for the same outcomes (e.g., progression-free survival), which often stems from analysis choices regarding which events to consider as part of the composite endpoint, censoring or competing risk in the analysis. Subsequent therapies such as hematopoietic stem cell transplantation are common but are not treated the same in different studies. Standard survival analysis methods are commonly applied to TTE analyses but often without full consideration of the assumptions inherent in the chosen analysis. We highlight two important issues of TTE analysis that arise in CAR-T studies, as well as in other settings in oncology: the handling of competing risks and assessing the association between a time-varying (post-infusion) exposure and the TTE outcome. We review existing analytical methods, including the cumulative incidence function and regression models for analysis of competing risks, and landmark and time-varying covariate analysis for analysis of post-infusion exposures. We clarify the scientific questions that the different analytical approaches address and illustrate how the application of an inappropriate method could lead to different results using data from multiple published CAR-T studies. Codes for implementing these methods in standard statistical software are provided.

Cause of death and cause-specific mortality for primary liver cancer in South Korea: A nationwide population-based study in hepatitis B virus-endemic area.

Background/AimsPrimary liver cancer is one of the leading causes of cancer mortality worldwide. However, the causes of death have not been studied in detail in patients with liver cancer.MethodsThe causes of death and cause-specific mortality risks in patients with primary liver cancer, diagnosed during 2000–2016, were investigated using the nationwide population-based cancer registry data in South Korea (n=231,388). The cumulative incidence function and Fine-Gray models were used to estimate the cause-specific mortality under the competing risks. Risks of non-cancer deaths relative to the general population were compared by standardized mortality ratios (SMRs).ResultsAmong 179,921 total deaths, 92.4%, 1.7%, and 6.0% of patients died of primary liver cancer, cancer from other sites, and non-cancer illnesses, respectively. Proportionate mortality from liver cancer remained high. The 5-year competing risks probability of death from liver cancer varied by tumor stage, from 42% to 94%, and it remained high 10 years after the diagnosis (61–95%). Competing mortality from other causes has continuously increased. The most common non-cancer causes of death were underlying liver diseases (SMR, 15.6; 95% confidence interval [CI], 15.1–16.1) and viral hepatitis (SMR, 46.5; 95% CI, 43.9–49.2), which demonstrated higher mortality risks compared to the Korean general population. Higher mortality risks of suicide (SMR, 2.6; 95% CI, 2.4–2.8) was also noted.ConclusionsPatients with liver cancer are most likely to die from liver cancer and related liver disease, even 10 years after the diagnosis, highlighting a need for specialized long-term follow-up care.

The Neutrophil to Lymphocyte Ratio Is Associated With the Risk of Subsequent Dementia in the Framingham Heart Study.

Objective: Active neutrophils are important contributors to Alzheimer’s disease (AD) pathology through the formation of capillary stalls that compromise cerebral blood flow (CBF) and through aberrant neutrophil signaling that advances disease progression. The neutrophil to lymphocyte ratio (NLR) is a proxy of neutrophil-mediated inflammation, and higher NLR is found in persons diagnosed with clinical AD. The objective of this study was to investigate whether increased NLR in older adults is independently associated with the risk of subsequent dementia.Methods: We examined associations of baseline NLR with incident dementia risk in the community-based Framingham Heart Study (FHS) longitudinal cohorts. The association between NLR and risk of dementia was evaluated using the cumulative incidence function (CIF) and inverse probability-weighted Cox proportional cause-specific hazards regression models, with adjustment for age, sex, body mass index (BMI), systolic and diastolic blood pressure, diabetes, current smoking status, low-density lipoprotein (LDH), high-density lipoprotein (LDL), total cholesterol, triglycerides, and history of cardiovascular disease (CVD). Random forest survival models were used to evaluate the relative predictive value of the model covariates on dementia risk.Results: The final study sample included 1,648 participants with FHS (average age, 69 years; 56% women). During follow-up (median, 5.9 years), we observed 51 cases of incident dementia, of which 41 were AD cases. Results from weighted models suggested that the NLR was independently associated with incident dementia, and it was preceded in predictive value only by age, history of CVD, and blood pressure at baseline.Conclusion: Our study shows that individuals with higher NLR are at a greater risk of subsequent dementia during a 5.9-year follow-up period. Further evaluating the role of neutrophil-mediated inflammation in AD progression may be warranted.

Abstract 10518: Impact of Managing Provider Type on Severe Aortic Stenosis Referral and Treatment Patterns: An Optum Electronic Medical Records Analysis

A significant proportion of patients diagnosed with symptomatic severe aortic stenosis (ssAS) do not receive treatment with aortic valve replacement (AVR) despite current ACC/AHA guidelines. Delayed care leads to increased hospitalizations, worsening heart failure and death. Timely referral to a cardiac specialist is a critical step in the treatment pathway. We sought to identify the impact of managing provider type on follow-up care for newly diagnosed patients with severe aortic stenosis (sAS). We analyzed Optum® electronic medical records to identify adults with a new outpatient sAS echo diagnosis in the pre-COVID era (1/2017 - 3/2019). We identified integrated delivery network patients alive 1d post echo excluding those with missing data or AVR within 3d of echo, then selected those managed by a primary care provider (PCP) or a cardiologist (n=5,683). Baseline characteristics were used for covariate-adjusted Cumulative Incidence Function and Fine-Gray subdistribution hazard models. We estimated the impact of managing provider type on the specialist follow-up visit rate (cardiologist, interventional cardiologist and/or cardiothoracic surgeon) for all sAS patients and of surgical or transcatheter AVR for ssAS patients within 1 year of diagnosis. Within 90d of sAS diagnosis, 47% of PCP- vs. 73% of cardiologist-managed patients had a follow-up visit (1-year rates: PCP, 69% vs. cardiologist, 90%; Hazard ratio [HR]=0.54, 95% confidence interval [CI]: 0.49-0.59, p&lt;0.0001). Within 1 year of diagnosis, 36% of PCP- vs. 51% of cardiologist-managed ssAS patients underwent AVR (HR=0.72, CI: 0.63-0.82, p&lt;0.0001) (Figure). Analysis suggests lower referral rates for PCP- than cardiologist-managed patients. In ssAS, 1-year AVR rates were low, particularly for PCPs. These data underscore the importance of timely follow up of all severe AS patients for symptom assessment and appropriate treatment, presenting an opportunity for initiatives to drive behavior change.

Insomnia symptoms are associated with an increased risk of type 2 diabetes mellitus among adults aged 50 and older.

To evaluate the association of the different degrees of insomnia symptoms with subsequent incidence of type 2 diabetes mellitus (T2DM). The data were extracted from Health and Retirement Study 2006-2014 waves. The association of insomnia symptoms with T2DM incidence was evaluated by the competing risk model with cumulative incidence function (death was considered a competing event) and Cox proportional hazard model with the Kaplan-Meier method. Population attributable fraction (PAF) was calculated. All analyses related to our study were conducted between November 2020 and January 2021. A total of 14,112 patients were included in this study, with an average follow-up of 6.4years, and the incidence density was 17.9 per 1000 person-years. Insomnia symptoms were positively associated with T2DM incidence compared with those with no insomnia symptoms, regardless of competing risk model (≥ 1 symptoms: sub-distribution hazard ratio (SHR) 1.13; 95% confidence interval (CI) 1.02-1.26; P-trend = 0.012) and Cox proportional hazard model (≥ 1 symptoms: hazard ratio (HR) 1.13; 95% CI 1.02-1.26; P-trend = 0.013). The cumulative incidence function (Gray's test, p < 0.001) and Kaplan-Meier estimate (log-rank test, p < 0.001) also presented this positive relationship. This positive association was more apparent in women and participants with ages from 50 to 65 years. The PAF was 4.1% with 95% CI (0.7-7.9%). Insomnia symptoms may be an important risk factor for the development of T2DM, which is unbiased by the death competing risk. These findings suggest that management of sleep problems may be an important part of strategies to prevent T2DM.

Competing risk model to determine the prognostic factors and treatment strategies for elderly patients with glioblastoma

The prognostic factors and optimal treatment for the elderly patient with glioblastoma (GBM) were poorly understood. This study extracted 4975 elderly patients (≥ 65 years old) with histologically confirmed GBM from Surveillance, Epidemiology and End Results (SEER) database. Firstly, Cumulative incidence function and cox proportional model were utilized to illustrate the interference of non-GBM related mortality in our cohort. Then, the Fine-Gray competing risk model was applied to determine the prognostic factors for GBM related mortality. Age ≥ 75 years old, white race, size > 5.4 cm, frontal lobe tumor, and overlapping lesion were independently associated with more GBM related death, while Gross total resection (GTR) (HR 0.87, 95%CI 0.80–0.94, P = 0.010), radiotherapy (HR 0.64, 95%CI 0.55–0.74, P < 0.001), chemotherapy (HR 0.72, 95%CI 0.59–0.90, P = 0.003), and chemoRT (HR 0.43, 95%CI 0.38–0.48, P < 0.001) were identified as independently protective factors of GBM related death. Based on this, a corresponding nomogram was conducted to predict 3-, 6- and 12-month GBM related mortality, the C-index of which were 0.763, 0.718, and 0.694 respectively. The calibration curve showed that there was a good consistency between the predicted and the actual mortality probability. Concerning treatment options, GTR followed by chemoRT is suggested as optimal treatment. Radiotherapy and chemotherapy alone also provide moderate clinical benefits.

The Effect of a Cancer History on Patients with Acute Myocardial Infarction After Percutaneous Coronary Intervention

The effect of a history of cancer on the prognosis of patients with acute myocardial infarction (AMI) after percutaneous coronary intervention (PCI) is poorly understood.From the Osaka Acute Coronary Insufficiency Study (OACIS) registry in Osaka, Japan, we enrolled the case data of a total of 3499 patients with AMI treated with PCI between 1998 and 2014, of whom 462 had a cancer history (cancer group, 13.2%) and 3037 did not (non-cancer group, 86.8%). All of the cases were followed for up to five years from discharge.The Kaplan-Meier curve and multivariate analysis using Cox proportional hazards models revealed that all-cause mortality was significantly higher in the cancer group than in the non-cancer group (adjusted hazard ratio [HR], 2.43; P < 0.001). Deaths from cardiac, cancer, and other causes were treated as competing events, and competing analysis using the cumulative incidence function (CIF) and Fine-Gray model revealed that mortality due to cancer was higher in the cancer group than in the non-cancer group, whereas cardiac mortality was similar between the two groups. The incidences of cardiovascular events, including stroke, recurrent infarction, and heart failure requiring readmission, were also similar between the two groups, although the Kaplan-Meier analysis and univariate Cox proportional hazards model revealed that the incidence of stroke was higher in the cancer group than in the non-cancer group.A history of cancer increased all-cause and cancer mortality among patients with AMI treated with PCI, although it was not associated with cardiovascular events.

Prognostic value of KRAS mutation status in colorectal cancer patients: a population-based competing risk analysis.

BackgroundTo use competing analyses to estimate the prognostic value of KRAS mutation status in colorectal cancer (CRC) patients and to build nomogram for CRC patients who had KRAS testing.MethodThe cohort was selected from the Surveillance, Epidemiology, and End Results database. Cumulative incidence function model and multivariate Fine-Gray regression for proportional hazards modeling of the subdistribution hazard (SH) model were used to estimate the prognosis. An SH model based nomogram was built after a variable selection process. The validation of the nomogram was conducted by discrimination and calibration with 1,000 bootstraps.ResultsWe included 8,983 CRC patients who had KRAS testing. SH model found that KRAS mutant patients had worse CSS than KRAS wild type patients in overall cohort (HR = 1.10 (95% CI [1.04–1.17]), p < 0.05), and in subgroups that comprised stage III CRC (HR = 1.28 (95% CI [1.09–1.49]), p < 0.05) and stage IV CRC (HR = 1.14 (95% CI [1.06–1.23]), p < 0.05), left side colon cancer (HR = 1.28 (95% CI [1.15–1.42]), p < 0.05) and rectal cancer (HR = 1.23 (95% CI [1.07–1.43]), p < 0.05). We built the SH model based nomogram, which showed good accuracy by internal validation of discrimination and calibration. Calibration curves represented good agreement between the nomogram predicted CRC caused death and actual observed CRC caused death. The time dependent area under the curve of receiver operating characteristic curves (AUC) was over 0.75 for the nomogram.ConclusionThis is the first population based competing risk study on the association between KRAS mutation status and the CRC prognosis. The mutation of KRAS indicated a poor prognosis of CRC patients. The current competing risk nomogram would help physicians to predict cancer specific death of CRC patients who had KRAS testing.

Sex differences in HIV treatment outcomes and adherence by exposure groups among adults in Guangdong, China: A retrospective observational cohort study

IntroductionWe aimed to assess sex differences in treatment outcomes and adherence comparing men who have sex with women (MSW), men who have sex with men (MSM), and women who have sex with men (WSM), as well as men and women who inject drugs living with HIV on combination antiretroviral therapy (ART) in Guangdong, China. MethodsWe performed a retrospective observational cohort study with data from the National Free Antiretroviral Treatment Program database. We included ART-naive patients aged 18 to 80 years who had contracted HIV through sex or injecting drugs, initiated first-line ART between January 2004 and December 2016, and had at least 60 days of follow-up. Participants were followed for five years. Kaplan-Meier analysis and Cox proportional hazard models were used to evaluate all-cause mortality. Cumulative incidence function and Cox proportional hazards models accounting for competing risks were used to evaluate disease progression to AIDS. Modified Poisson regression models were used to evaluate immunological and virological responses and loss to follow-up. Repeated measures analysis was used to evaluate regular CD4+ cell count, HIV viral load monitoring, ART adherence, side effects, and interruption of ART. FindingsWe included 26,409 persons living with HIV. 21,779 (82·5%) people acquired HIV through sex (5118 WSM [23·5%], 8506 MSW [39·0%], 8175 MSM [37·5%]), and 4610 people (17·5%) through injection drug use (249 women [5·4%], 4361 men [94·6%]). Among those infected through sex, MSW had increased risks of all-cause mortality (adjusted hazard ratio [aHR] 1·48, 95% CI 1·20–1·83), progression to AIDS (1·27, 1·09–1·47), virological failure (adjusted incidence rates ratio [aIRR] 1·27, 95% CI 1·09–1·48), and loss to follow-up (1·22, 1·10–1·35) compared to WSM. In contrast, MSM had lower risk of all-cause mortality (aHR 0·49, 95%CI 0·32–0·76), disease progression to AIDS (0·83, 0·68–1·00), and virological failure (aIRR 0·78, 95%CI 0·65–0·94), were more likely to receive regular CD4+ cell count (1·08, 1·07–1·10) and HIV viral load monitoring (1·13, 1·12–1·15), were less likely to report missing ART doses (0·54, 0·49–0·61), interrupt ART (0·34, 0·26–0·44), or be lost to follow-up (0·56, 0·49–0·65) compared to WSM. Men who inject drugs were almost twice as likely as women who inject drugs to die (aHR 1·72, 95%CI 1·03–2·85), experience disease progression to AIDS (2·05, 1·18–3·57), virological failure (aIRR 1·81, 95%CI 1·19–2·76), report ART side effects (1·78, 1·43–2·22), and interruptions in ART (2·29, 1·50–3·50). InterpretationOur findings highlight the importance of identifying potentially at-risk MSW and promoting HIV education and testing among them. Particular attention is warranted among men who inject drugs to improve timely HIV diagnosis, drug interaction management, and retention in treatment. Additional research from rural settings is needed to assess the long-term treatment outcomes and adherence in MSM with HIV.

Gender Differences in Clinical Outcomes after Left Ventricular Assist Device (LVAD) Implantation - Does Device Strategy Matter?

Findings regarding outcomes after LVAD implantation in women and men are inconsistent, which may be due to combining data from patients differing in device strategy. The present analyses explored gender differences at baseline in medical and psychosocial patient characteristics and multiple clinical outcomes, stratified for patients bridged to transplantation (BTT) and those intended for destination therapy (DT). 8,461 patients in DT (20% women), and 11,189 patients in BTT (22% women), who received a primary continuous-flow LVAD between 6/2006 and 12/2017 and were registered with INTERMACS, were analyzed by device strategy and gender. Outcomes included death, transplant, device explant due to recovery, and device replacement due to complications. Associations of gender with time until each competing outcome were evaluated using cumulative incidence function and cause-specific Cox proportional hazard models, controlling for age, disease severity, hematological parameters, and psychosocial factors (e.g., marital status, social support, depression, history of alcohol abuse, and smoking). In both BTT and DT, women were younger, reported less substance abuse, were less likely to be white, married and working for an income, but more likely to be depressed than men. In BTT, men were more likely to be currently smoking, whereas in DT, women were more likely to be smoking. In DT, women were also more likely to be overweight. Regarding outcomes, during a mean follow up of 19 months, women had an increased rate of death compared to men in BTT [HR 1.11, 95% CI (1.00-1.23), p < .05], but not in DT [HR 1.01, 95% CI (0.91-1.12)]; women's rate of device replacement, however was increased only in DT [HR 1.19, 95% CI (1.03-1.39), p < .05]. Only in BTT had women a lower rate to be transplanted than men [HR 0.83, 95% CI (0.76-0.90), p < .001]. In both BTT and DT, women had higher rates for explant due to heart function recovery than men, even after controlling for medical and psychosocial covariates [DT: HR 1.79, 95% CI (1.27-2.56), p < .01; BTT: HR 1.33 95% CI (1.00-1.79), p < .05]. The results indicate that women and men differ in outcomes depending on intended device strategy. Thus, distinguishing between device strategies may help to understand gender differences in clinical outcomes after LVAD implantation.

Nomogram Predicting Cause-Specific Mortality in Nonmetastatic Male Breast Cancer: A Competing Risk Analysis

Introduction: Male breast cancer (MBC) is a rare tumor with few cases for research. Using the Surveillance, Epidemiology, and End Results program database, we carried out a competing risk analysis in patients with primary nonmetastatic MBC and built a predictive nomogram.Materials and Methods: We extracted primary nonmetastatic MBC patients according to the inclusion and exclusion criteria. Cumulative incidence function (CIF) and proportional subdistribution hazard model were adopted to explore risk factors for breast cancer-specific death (BCSD) and other cause-specific death (OCSD). Then we built a nomogram to predict the 3-year, 5-year and 8-year probabilities of BCSD and OCSD. C-indexes, Brier scores and calibration curves were chosen for validation.Results: We identified 1,978 nonmetastatic MBC patients finally. CIF analysis showed that the 3-year, 5-year and 8-year mortalities were 5.2%, 10.6% and 16.5% for BCSD, and 6.1%, 9.6% and 14.4% for OCSD. After adjustment of Fine and Gray models, black race, PR (-), advanced T/N/grade and no surgery were independently associated with BCSD. Meanwhile, elderly, unmarried status, advanced AJCC stage and no chemotherapy resulted in OCSD more possibly. A graphic nomogram was developed according to the coefficients from the Fine and Gray models. The calibration curves displayed exceptionally, with C-indexes nearly larger than 0.700 and Brier scores nearly smaller than 0.100.Conclusion: The competing risk nomogram showed good accuracy for predictive prognosis in nonmetastatic MBC patients. It was a useful implement to evaluate crude mortalities of BCSD and OCSD, and help clinicians to choose appropriate therapeutic plans.

Prognostic factors on outcomes of follicular thyroid cancer

We investigated the influences of prognostic factors on long-term survival of patients with follicular thyroid cancer (FTC) based on all-cause mortality and two exclusive causes of death, FTC and non-FTC. In this retrospective cohort study, we collected data of 204 patients with FTC diagnosed between 1985 and 2007at National Taiwan University Hospital. For all-cause mortality, Cox proportional hazards models were used to estimate hazard ratios for prognostic factors. Cause-specific hazard and cumulative incidence function models were used to determine the influences of prognostic factors on FTC and non-FTC death, respectively. The dynamic processes of distant metastases and locoregional recurrences were included as time-varying factors in all models. The cumulative incidence of all-cause death was 24% and 45% at 10 and 20-years, respectively. Multivariate analyses identified that distant metastases, locoregional recurrences, and positive surgical margins were significant independent risk factors for overall survival, hazard, and cumulative incidence of FTC death. Age at diagnosis >60 years increased the risks of all-cause and non-FTC death as well as cumulative incidence of non-FTC death. Tumor size >4cm had a harmful effect on overall survival. Female patients had higher risk and cumulative incidence of FTC death, but male patients had a higher cumulative incidence of non-FTC death. Lymph node metastases significantly increased the cumulative incidence of FTC death. Dynamic distant metastases and locoregional recurrences were the most dominant risk factors influencing FTC-specific hazard and cumulative incidence for FTC death by accounting for non-FTC death as a competing risk for FTC patients.

The impact of age at the time of radiotherapy for localized prostate cancer on the development of second primary malignancies

PurposeThere is a known increased risk of second primary malignancy (SPM) in patients with prostate cancer (CaP) treated with radiotherapy (RT). It is unclear how age at diagnosis influences the risk of SPMs. Materials and methodsUsing the 1973 to 2013 Surveillance, Epidemiology, and End Results Program, we studied the impact of age on SPMs (defined as a bladder or rectal tumor) after localized CaP treatment with radical prostatectomy (RP) or RT. SPM risk was compared using inverse probability of treatment weighting (IPTW)-adjusted cumulative incidence function and competing-risk proportional hazard models. Overall survival (OS) in patients with SPM was compared using Kaplan Meier and Cox regression analyses. ResultsA total of 579,608 patients met inclusion criteria, and 51.8% of the cohort was treated with RT. The 10- and 20-year cumulative incidences of competing risk (IPTW adjusted) of SPMs were 1.9% (95%CI = 1.8–1.9%) and 3.6% (95%CI = 3.4–3.7%) after RP vs. 2.7% (95%CI = 2.6–2.8%) and 5.4%(95%CI = 5.3–5.6%) after RT. IPTW-adjusted competing risk hazard ratio (HR) of SPM after RT compared to RP was increased in the entire cohort (HR 1.46; 95%CI = 1.39–1.53, P < 0.001) and was highest in the youngest patients: Age <55 HR = 1.83 (95% confidence interval [CI] = 1.49–2.24, P<0.001), Age 55 to 64 HR = 1.66 (95%CI = 1.54–1.79, P < 0.001), Age 65–74 HR = 1.41 (95%CI = 1.33–1.48, P < 0.001), Age ≥75 HR = 1.14 (95%CI = 0.97–1.35, P = 0.112). At 10 years, SPM-specific mortality occurred in 28.9% of patients treated with RT, though OS with SPM was worse in the youngest patients: Age <55 HR = 1.88 (95%CI = 1.25–2.81, P = 0.002), Age 55–64 HR = 1.60 (95%CI = 1.42–1.81, P < 0.001), Age 65–74 HR = 1.40 (95%CI = 1.30–1.52, P < 0.001), Age ≥ 75 HR = 1.27 (95%CI = 1.06–1.53, P = 0.009). All of the age categories had similar median follow-up times. ConclusionAt 10 years there is a 1.8% increased incidence of SPM after RT compared to RP, of which <30% of RT-treated patients with an SPM die as a result of a SPM. However, the risk of SPMs was greatest among younger men treated with RT for localized CaP, and this relationship could not be explained solely by follow-up time, latency time, or life expectancy. An improved understanding of those at the highest risk of SPMs may help tailor treatment and surveillance strategies.

Lemur species-specific metapopulation responses to habitat loss and fragmentation.

Determining what factors affect species occurrence is vital to the study of primate biogeography. We investigated the metapopulation dynamics of a lemur community consisting of eight species (Avahi occidentalis, Propithecus coquereli, Microcebus murinus, Microcebus ravelobensis, Lepilemur edwardsi, Cheirogaleus medius, Eulemur mongoz, and Eulemur fulvus) within fragmented tropical dry deciduous forest habitat in Ankarafantsika National Park, Madagascar. We measured fragment size and isolation of 42 fragments of forest ranging in size from 0.23 to 117.7 ha adjacent to continuous forest. Between June and November 2011, we conducted 1218 surveys and observed six of eight lemur species (M. murinus, M. ravelobensis, C. medius, E. fulvus, P. coquereli, and L. edwardsi) in the 42 fragments. We applied among patch incidence function models (IFMs) with various measures of dispersal and a mainland-island IFM to lemur species occurrence, with the aim of answering the following questions: 1) Do lemur species in dry deciduous forest fragments form metapopulations? 2) What are the separate effects of area (extinction risk) and connectivity/isolation (colonization potential) within a lemur metapopulation? 3) Within simulated metapopulations over time, how do area and connectivity/isolation affect occurrence? and 4) What are the conservation implications of our findings? We found that M. murinus formed either a mainland-island or an among patch metapopulation, M. ravelobensis formed a mainland-island metapopulation, C. medius and E. fulvus formed among patch metapopulations, and neither P. coquereli or L. edwardsi formed a metapopulation. Metapopulation dynamics and simulations suggest that area was a more consistent positive factor determining lemur species occurrence than fragment isolation and is crucial to the maintenance of lemur populations within this fragmented landscape. Using a metapopulation approach to lemur biogeography is critical for understanding how lemur species respond to forest loss and fragmentation.

The incidence function model as a tool for landscape-scale ecological impact assessments

Landscape-scale approaches to assessing the impact of land-use change on species' persistence are necessary because species depend on processes acting at varying scales, yet existing approaches to ecological impact assessment tend only to be site-based. A further major criticism of current ecological impact assessments is that they tend to be qualitative. Here we develop methods that apply the Incidence Function Model (IFM) in real urban planning contexts, by generating repeatable and comparable quantitative measures of ecological impacts. To demonstrate the methods for a case study (Nottingham, UK), we estimated landscape-scale measures of species' persistence that indicate metapopulation viability. We based these on Nottingham’s landscape when urban developments were recently proposed, then adjust the land cover to include the proposed developments, and also for two projected landscapes where 10% and 20% of the original natural or semi-natural land cover is lost. We find that the IFM shows promise as a tool for quantitative landscape-scale ecological impact assessment, depending on the size of the impact. We detected minimal differences in the species' viability measures between the original and post-development landscapes. This suggests that for small (around 2%) cumulative losses of natural/semi-natural space, current site-based approaches are sufficient. However, when the cumulative effect of continued development was modelled by increasing the losses of natural/semi-natural land cover to 10–20% of existing cover, the impact on many of the species studied was more substantial. This indicates that a landscape-scale approach is necessary for larger, prolonged and cumulative habitat losses.

The stochastic resonance for the incidence function model of metapopulation

A stochastic model with endogenous and exogenous periodicities is proposed in this paper on the basis of metapopulation dynamics to model the crop yield losses due to pests and diseases. The rationale is that crop yield losses occur because the physiology of the growing crop is negatively affected by pests and diseases in a dynamic way over time as crop both grows and develops. Metapopulation dynamics can thus be used to model the resultant crop yield losses. The stochastic metapopulation process is described by using the Simplified Incidence Function model (IFM). Compared to the original IFMs, endogenous and exogenous periodicities are considered in the proposed model to handle the cyclical patterns observed in pest infestations, diseases epidemics, and exogenous affecting factors such as temperature and rainfalls. Agricultural loss data in China are used to fit the proposed model. Experimental results demonstrate that: (1) Model with endogenous and exogenous periodicities is a better fit; (2) When the internal system fluctuations and external environmental fluctuations are negatively correlated, EIL or the cost of loss is monotonically increasing; when the internal system fluctuations and external environmental fluctuations are positively correlated, an outbreak of pests and diseases might occur; (3) If the internal system fluctuations and external environmental fluctuations are positively correlated, an optimal patch size can be identified which will greatly weaken the effects of external environmental influence and hence inhibit pest infestations and disease epidemics.

A metapopulation model with Markovian landscape dynamics

We study a variant of Hanski’s incidence function model that allows habitat patch characteristics to vary over time following a Markov process. The widely studied case where patches are classified as either suitable or unsuitable is included as a special case. For large metapopulations, we determine a recursion for the probability that a given habitat patch is occupied. This recursion enables us to clarify the role of landscape dynamics in the survival of a metapopulation. In particular, we show that landscape dynamics affects the persistence and equilibrium level of the metapopulation primarily through its effect on the distribution of a local population’s life span.