Many breast cancer diagnoses and second cancers are associated with BRCA gene mutations. Early detection of cancer is necessary to improve health outcomes, particularly with second cancers. Little is known about the influence of risk factors on time to diagnosis of second primary cancers after diagnosis with BRCA-related breast cancer. The purpose of this cohort study was to examine the risk of diagnosis of second primary cancers among women diagnosed with breast cancer after adjusting for BRCA status, age, and ethnicity. The study was guided by the empirical evidence supporting the mechanism of action in the mutation of BRCA leading to the development of cancer. Composite endpoint was used to define second primary cancer occurrences, and Kaplan-Meier survival curves were used to compare the median time-to-event among comparison groups and BRCA gene mutation status. Cox proportional hazards was used to examine the relationships between age at diagnosis, ethnicity, BRCA gene mutation status, and diagnosis of a second primary cancer. The overall median time to event for diagnosis of second primary cancers was 14 years. The hazard ratios for BRCA2 = 1.47, 95% CI [1.03 - 2.11], White = 1.511, 95% CI [1.18 - 1.94], and American Indian/Hawaiian = 1.424, 95% CI [1.12 -1.81] showing positive significant associations between BRCA2 mutation status and risk of diagnosis of second primary colorectal, endometrial, cervical, kidney, thyroid, and bladder cancers. Data on risk factors for development of second cancers would allow for identification of appropriate and timely screening procedures, determining the best course of action for prevention and treatment, and improving quality of life among breast cancer survivors.

In survival analysis interest often lies in the relationship between the survival function and a certain number of covariates. It usually happens that for some individuals we cannot observe the event of interest, due to the presence of right censoring and/or left truncation. A typical example is given by a retrospective medical study, in which one is interested in the time interval between birth and death due to a certain disease. Patients who die of the disease at early age will rarely have entered the study before death and are therefore left truncated. On the other hand, for patients who are alive at the end of the study, only a lower bound of the true survival time is known and these patients are hence right censored. In the case of censored and/or truncated responses, lots of models exist in the literature that describe the relationship between the survival function and the covariates (proportional hazards model or Cox model, log-logistic model, accelerated failure time model, additive risks model, etc.). In these models, the regression coefficients are usually supposed to be constant over time. In practice, the structure of the data might however be more complex, and it might therefore be better to consider coefficients that can vary over time. In the previous examples, certain covariates (e.g. age at diagnosis, type of surgery, extension of tumor, etc.) can have a relatively high impact on early age survival, but a lower influence at higher age. This motivated a number of authors to extend the Cox model to allow for time-dependent coefficients or consider other type of time-dependent coefficients models like the additive hazards model. In practice it is of great use to have at hand a method to check the validity of the above mentioned models. First we consider a very general model, which includes as special cases the above mentioned models (Cox model, additive model, log-logistic model, linear transformation models, etc.) with time-dependent coefficients and study the parameter estimation by means of a least squares approach. The response is allowed to be subject to right censoring and/or left truncation. Secondly we propose an omnibus goodness-of-fit test that will test if the general time-dependent model considered above fits the data. A bootstrap version, to approximate the critical values of the test is also proposed. In this dissertation, for each proposed method, the finite sample performance is evaluated in a simulation study and then applied to a real data set.

Darbo metu buvo išnagrinėta įvairių faktorių (kovariančių) įtaka reumatoidiniu artritu sergančio 531 ligonio mirtingumui. Buvo taikomas vienas iš regresinių išgyvenamumo modelių – Cox’o modelis. Iš minėtos 531 ligonio imties mirę buvo 32 ligoniai. Iš pradžių buvo tiriama ligonių imtis laiko nuo ligos pradžios aspektu. Šiuo atveju prognozuojantys veiksniai buvo amžius, kada liga buvo diagnozuota (AMZDGN), lytis (LYTKOD), gydymas Metotreksatu (GYD_MTX) ir gydymas Azatriopinu/Imuranu (AZA_IMUR). Vėliau, tiriant ligonių mirtingumą kaip amžiaus funkciją, nustatyti svarbiausi lemiantys veiksniai buvo šie: ligonių lytis (LYTKOD) ir gydymas Azatriopinu/Imuranu (AZA_IMUR). Gauti rezultatai, t.y. ligonių išgyvenamumą lemiančios kovariantės (veiksniai), beveik visiškai sutampa su gydytojų nurodytais. Tai dar kartą patvirtina matematinių statistinių modelių, šiuo atveju nagrinėjamo Cox‘o modelio, taikymo realiame gyvenime, svarbą. Kitai duomenų imčiai, t.y. vėžiu sergančių ligonių duomenų aibei, buvo taikomas Persikertančių mirimų intensyvumų (SCE) modelis, t.y. tikrinama Cox‘o modelio adekvatumo duomenims hipotezė. Hipotezė buvo atmesta, nes minėtiems duomenims Cox‘o modelis negalioja. Pagrindinis darbo rezultatas yra šis: gautas kriterijus Cox‘o modelio adekvatumui tikrinti, naudojant nupjautus iš kairės ir cenzūruotus iš dešinės duomenis, sudarytos programos kriterijui realizuoti. Reumatoidinio artrito ligonių duomenų aibei, t.y. nupjautiems iš kairės ir cenzūruotiems iš dešinės... [toliau žr. visą tekstą] / In this work the Cox proportional hazards model was applied to investigate the influence of various factors (covariates) to mortality of rheumatoid arthritis patients of Vilnius. In the first case, the sample of 531 patients was analysed. Analysing survival of patients of the sample as function of time from the beginnig of the disease, the prognostic factors were LYTKOD (the sex of patients), AMZDGN (patients‘ age, when the rheumatoid arthritis was diagnosed), GYD_MTX (treatment with metotrexat) and AZA_IMUR (treatment with Azatriopin/Imuran). When survival was analysed as function of age then the prognostic factor were LYTKOD (the sex of patients) and AZA_IMUR (treatment with Azatriopin/Imuran). The results are almost identical to those, which doctors suggested. This fact confirms the importance of using mathematical statistical models to solve the problems of the real life. In this case, the importance of using the Cox model. On the other hand, Simple cross-effects (SCE) model was aplied for the sample of canser patients. In the case of this model the hypothesis of Cox model fiting for canser patients‘ data was rejected. The most important result of this work is that the criterion of Cox model fitting to left truncated and right censored data was constructed. Also a program of SAS for the criterion was created. The the hypothesis of Cox model fiting for the rheumatoid arthritis patients wasn‘t rejected, because Cox model fit for these data.

Made available in DSpace on 2014-12-17T15:34:49Z (GMT). No. of bitstreams: 1 DeborahGPG_DISSERT.pdf: 1421770 bytes, checksum: da1c0ade32fb8610306243b0cf52f13d (MD5) Previous issue date: 2014-02-20 / Coordena??o de Aperfei?oamento de Pessoal de N?vel Superior / Among the traits of economic importance to dairy cattle livestock those related to sexual precocity and longevity of the herd are essential to the success of the activity, because the stayability time of a cow in a herd is determined by their productive and reproductive lives. In Brazil, there are few studies about the reproductive efficiency of Swiss-Brown cows and no study was found using the methodology of survival analysis applied to this breed. Thus, in the first chapter of this study, the age at first calving from Swiss-Brown heifers was analyzed as the time until the event by the nonparametric method of Kaplan-Meier and the gamma shared frailty model, under the survival analysis methodology. Survival and hazard rate curves associated with this event were estimated and identified the influence of covariates on such time. The mean and median times at the first calving were 987.77 and 1,003 days, respectively, and significant covariates by the Log-Rank test, through Kaplan-Meier analysis, were birth season, calving year, sire (cow s father) and calving season. In the analysis by frailty model, the breeding values and the frailties of the sires (fathers) for the calving were predicted modeling the risk function of each cow as a function of the birth season as fixed covariate and sire as random covariate. The frailty followed the gamma distribution. Sires with high and positive breeding values possess high frailties, what means shorter survival time of their daughters to the event, i.e., reduction in the age at first calving of them. The second chapter aimed to evaluate the longevity of dairy cows using the nonparametric Kaplan-Meier and the Cox and Weibull proportional hazards models. It were simulated 10,000 records of the longevity trait from Brown-Swiss cows involving their respective times until the occurrence of five consecutive calvings (event), considered here as typical of a long-lived cow. The covariates considered in the database were age at first calving, herd and sire (cow s father). All covariates had influence on the longevity of cows by Log-Rank and Wilcoxon tests. The mean and median times to the occurrence of the event were 2,436.285 and 2,437 days, respectively. Sires that have higher breeding values also have a greater risk of that their daughters reach the five consecutive calvings until 84 months / Dentre as caracter?sticas de import?ncia econ?mica para a pecu?ria leiteira aquelas relacionadas com a precocidade sexual e a longevidade do rebanho s?o determinantes para o sucesso da atividade, uma vez que o tempo de perman?ncia de uma vaca num rebanho ? determinado por suas vidas produtiva e reprodutiva. No Brasil, existem poucos estudos sobre a efici?ncia reprodutiva de vacas Pardo-Su??as e n?o foi encontrado nenhum estudo abordando o uso da metodologia de an?lise de sobreviv?ncia aplicada a esta ra?a. Assim, no primeiro cap?tulo deste trabalho, a idade ao primeiro parto de novilhas Pardo-Su??as foi analisada como o tempo at? o evento por meio do m?todo n?o-param?trico de Kaplan-Meier e do modelo de fragilidade compartilhado gama, sob a metodologia de an?lise de sobreviv?ncia. Foram estimadas curvas de sobreviv?ncia e de taxa de risco associadas com este evento e verificada a influ?ncia das covari?veis consideradas sobre o tempo. Os tempos m?dio e mediano ao primeiro parto foram 987,77 e 1.003 dias, respectivamente; e as covari?veis significativas pelo teste de Log-Rank, na an?lise por Kaplan-Meier, foram esta??o de nascimento, ano de parto, touro (pai da vaca) e esta??o de parto. Na an?lise pelo modelo de fragilidade, foram preditos os valores gen?ticos e as fragilidades dos touros (pais) para o parto, modelando-se a fun??o de risco de cada vaca em fun??o da covari?vel fixa esta??o de nascimento e da covari?vel aleat?ria touro. A fragilidade seguiu a distribui??o gama. Touros com valores gen?ticos positivos e altos possuem fragilidades altas, o que significa menor tempo de sobreviv?ncia de suas filhas ao evento, ou seja, redu??o na idade ao primeiro parto delas. O segundo cap?tulo teve como objetivo avaliar a longevidade de vacas leiteiras utilizando o estimador n?o-param?trico de Kaplan-Meier e os modelos de riscos proporcionais de Weibull e de Cox. Foram simulados 10.000 registros da caracter?stica longevidade de f?meas Pardo-Su??as denotando seus respectivos tempos at? a ocorr?ncia de cinco partos consecutivos (evento), considerados aqui como t?picos de uma vaca longeva. As covari?veis consideradas no banco de dados foram a idade da vaca ao primeiro parto, o rebanho e o pai da vaca. Todas as covari?veis exerceram influ?ncia sobre a longevidade das vacas de acordo com os testes de Log-Rank e Wilcoxon. Os tempos m?dio e mediano para a ocorr?ncia do evento foram de 2.436,285 e 2.437 dias. Touros com maior valor gen?tico tamb?m possuem um maior risco de que as suas filhas alcancem os cinco partos aos 84 meses

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This paper presents an approach to model the risks associated with defaults, prepayments, and order returns in the context of unsecured consumer credits, specifically in buy-now-pay-later (BNPL) loans. The paper presents a Bayesian competing risk proportional hazard model to model the time to default, prepayment, and order return in BNPL loans. Model parameters are estimated using Markov chain Monte Carlo (MCMC) sampling techniques and Bayesian inference is developed using a unique dataset containing monthly performance data of fixed-duration interest-bearing consumer loans. / I denna rapport presenteras en metod för att modellera riskerna förknippade med fallissemang, förskottsbetalning, och returnering av order i osäkrade konsumentkrediter, mer specifikt i köp-nu-betala-senare (BNPL) krediter. Rapporten presenterar en Bayesiansk konkurrerande utfall-modell (competing risk) för att estimera tiden till fallissemang, förskottsbetalning och retur av order i BNPL-lån. Modellens parametrar estimeras med hjälp av Markov chain Monte Carlo (MCMC) metoder och Bayesiansk inferens uppnås med hjälp av ett unikt dataset med månatlig kassaflödesdata från räntebärande BNPL-lån.

Background: Data on the impact of gender on mortality after radical cystectomy is conflicting. We investigated a large single center sample with long-term follow-up in order to determine the relationship between gender and outcome. Patients and Methods: A total of 1,184 consecutive patients who underwent radical cystectomy for high risk superficial or muscle-invasive urothelial or undifferentiated bladder cancer between 1993 and 2015 were stratified by gender. Demographic data was compared using Mann-Whitney U test, chi-square test, or Fisher exact test. Cox proportional hazard models were used for the analysis of competing risks and logit models were used for the prediction of the receipt of adjuvant cisplatin-based chemotherapy. Results: Female patients were older, healthier, less frequently current smokers and had more extravesical tumors. In the multivariate analyses, female gender was an independent predictor of (lower) non-bladder cancer (competing) mortality (hazards ratio [HR] 0.68, 95% CI 0.49–0.95, p = 0.0248) but no predictor of bladder cancer-specific mortality (HR in the full model 1.20, 95% CI 0.94–1.54, p = 0.15). Gender was no predictor of the receipt of adjuvant cisplatin-based chemotherapy. Conclusions: Female gender was associated with an increased risk of extravesical disease but was no independent predictor of bladder cancer-specific mortality. Anatomical differences might be a plausible explanation for these observations.

Denna uppsats har undersökt tid-till-försäljning på Uppsala kommuns bostadsmarknad för lägenheter under året 2021. För att analysera tid-till-försäljning har metoder från överlevnadsanalys använts. Överlevnadsfunktionen och den kumulativa hasardfunktionen har skattats med Kaplan-Meier-skattningen och Nelson-Aalen-skattningen. Därutöver har tre modeller skattats; en Cox proportionell hasardmodell och två 'Accelerated Failure Time'-modeller varav en var en Weibullmodell och en var en Loglogistiskmodell. Resultaten indikerar att tid-till-försäljning har en hög hasard efter två veckor på marknaden varefter en avtagande hasard. Resultaten indikerar att kovariat har en statistisk signifikant effekt på tid-till-försäljning. Grafiska tester indikerar att antagandet om proportionalitet för Cox proportionella hasardmodell och antagandet om den underliggande hasardfunktionen för Weibullmodellen är orimliga. Antagandet om den underliggande hasardfunktionen för loglogistiskamodellen verkar rimlig. Goodness-of-fit indikerar att Weibullmodellen och loglogistiskamodellen var mer välanpassade till datamaterialet än Cox proportionella hasardmodell. / This bachelor's thesis has investigated time-to-sale on the Uppsala municipality property market for apartments during 2021. Analysis has been performed utilising methods from survival analysis. Both the survival function and cumulative hazard function were estimated using the Kaplan-Meier estimate and the Nelson-Aalen estimate respectively. Furthermore, three models were estimated; a Cox Proportional Hazards model as well as two Accelerated Failure Time models of which one was a Weibullmodell and the other was a loglogistic model. The results indicate that time-to-sale has a high hazard after two weeks on the market followed by a decreasing hazard. The results also indicate that covariates have a statistically significant effect on time-to-sale. Graphical tests indicate that the assumption of proportionality for the Cox Proportional Hazards model and the assumption of the underlying hazard function for the Weibullmodell are unreasonable. The assumed hazardfunction of the loglogistic model was found to be reasonable. Goodness of fit indicates that the Weibull model and loglogistic model were a better fit to the data than the Cox proportional Hazardsmodel.

如何藉由DNA微陣列資料跟存活資料的資訊來找出基因表現定型一直是個重要的議題。這些研究的主要目標是從大量的基因中找出那些真正跟存活時間或其它重要的臨床結果有顯著關係的小部分。Threshold Gradient Directed Regularization (TGDR)是ㄧ種已經被應用在高維度迴歸問題中能同時處理變數選取以及模型配適的演算法。然而，TGDR採用一種梯度投影型態的演算法使得收斂速率緩慢。在本篇論文中，我們建議新的包含Newton-Raphson求解演算法類型的改良版TGDR方法。我們建議的方法有類似TGDR的特性但卻有比較快的收斂速率。文中並利用一筆附有設限存活時間的真實微陣列癌症資料來做示範。 本篇論文的第二部份是關於適用於區間設限存活資料的重複抽樣Peto-Peto檢定。這個重複抽樣Peto-Peto檢定能夠評估存活函數估計方法的檢定力，例如Turnbull的估計方法以及Kaplan-Meier的估計方法。這個檢定方法顯示出在區間設限資料時Kaplan-Meier的估計方法的檢定力要比Turnbull的估計方法的檢定力來得低。這個檢定方法將以模擬的區間設限資料以及一筆真實關於乳癌研究的區間設限資料來說明。 / Analyzing censored survival data with high-dimensional covariates arising from the microarray data has been an important issue. The main goal is to find genes that have pivotal influence with patient's survival time or other important clinical outcomes. Threshold Gradient Directed Regularization (TGDR) method has been used for simultaneous variable selection and model building in high-dimensional regression problems. However, the TGDR method adopts a gradient-projection type of method and would have slow convergence rate. In this thesis, we proposed Modified TGDR algorithms which incorporate Newton-Raphson type of search algorithm. Our proposed approaches have the similar characteristics with TGDR but faster convergence rates. A real cancer microarray data with censored survival times is used for demonstration. The second part of this thesis is about a proposed resampling based Peto-Peto test for survival functions on interval censored data. The proposed resampling based Peto-Peto test can evaluate the power of survival function estimation methods, such as Turnbull’s Procedure and Kaplan-Meier estimate. The test shows that the power based on Kaplan-Meier estimate is lower than that based on Turnbull’s estimation on interval censored data. This proposed test is demonstrated on simulated data and a real interval censored data from a breast cancer study.

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