Frailty multi-state models for the analysis of survival data from multicenter clinical trials

Proportional hazards models are among the most popular regression models in survival analysis. Multi-state models generalise them in the sense of jointly considering different types of events along with their interrelations, whereas frailty models introduce random effects to account for unobserved risk factors, possibly shared by groups of subjects. The integration of frailty and multi-state methodology is interesting to control for unobserved heterogeneity in presence of complex event history structures, particularly appealing in multicenter clinical trials applications. In the present thesis we propose the incorporation of nested frailties in the transition-specific hazard function; then, we develop and evaluate both parametric and semi-parametric inference. Simulation studies, performed thanks to an innovative method for generating dependent multi-state survival data, show that parametric inference is correct but extremely imprecise, whilst semiparametric methods are very competitive to evaluate the effect of covariates. Two case studies are presented, relative to cancer multicenter clinical trials. The multi-state nature of the models allows to study the treatment effect taking into account intermediate events, while the presence of frailties reduces the attenuation effect due to clustering. Finally, we present two new software tools, one to fit parametric frailty models with up to twenty possible combinations of baseline and frailty distributions, and one implementing semiparametric inference for multilevel frailty models, essential to fit the new nested frailty multi-state models

Deep Neural Networks for Semiparametric Frailty Models via H-likelihood

For prediction of clustered time-to-event data, we propose a new deep neural network based gamma frailty model (DNN-FM). An advantage of the proposed model is that the joint maximization of the new h-likelihood provides maximum likelihood estimators for fixed parameters and best unbiased predictors for random frailties. Thus, the proposed DNN-FM is trained by using a negative profiled h-likelihood as a loss function, constructed by profiling out the non-parametric baseline hazard. Experimental studies show that the proposed method enhances the prediction performance of the existing methods. A real data analysis shows that the inclusion of subject-specific frailties helps to improve prediction of the DNN based Cox model (DNN-Cox)

Urological Cancer 2021

Cancer of the urological sphere is a disease continuously increasing in numbers in the statistics of tumor malignancies in Western countries. Although this fact is mainly due to the contemporary increase of life expectancy of the people in these geographic areas, many other factors do contribute as well to this growth. Urological cancer is a complex and varied disease of different organs and mainly affects the male population. In fact, kidney, prostate, and bladder cancer are regularly included in the top-ten list of the most frequent neoplasms in males in most statistics. The female population, however, has also increasingly found itself affected by renal and bladder cancer in the last decade. Considering these altogether, urological cancer is a problem of major concern in developed societies. This Topic Issue of Cancers intends to shed some light into the complexity of this field and will consider all useful and appropriate contributions that scientists and clinicians may provide to improve urological cancer knowledge for patients’ benefit. The precise identification of the molecular routes involved, the diagnostic pathological criteria in the grey zones, the dilemma of T1G3 management, and the possible treatment options between superficial, nonmuscle-invasive and muscle-invasive diseases will be particularly welcomed in this Issue

Interval-censored semi-competing risks data: a novel approach for modelling bladder cancer

Aquesta tesi tracta sobre tècniques d'anàlisi de supervivència en situacions amb múltiples esdeveniments i patrons complexes de censura. Proposem una nova metodologia per tractar la situació de riscos semi-competitius quan les dades estan censurades en un interval. La motivació del treball neix de la nostra col·laboració amb l'Estudi Espanyol del Càncer de Bufeta (SBC/EPICURO), el més gran estudi sobre càncer de bufeta realitzat fins ara a l'Estat Espanyol. La nostra contribució en el projecte es centra en la modelització i identificació de factors pronòstics de l'evolució de la malaltia.L'evolució de malalties complexes, com el càncer o la infecció VIH, es caracteritza per la ocurrència de múltiples esdeveniments en el mateix pacient: per exemple, la recaiguda de la malaltia o la mort. Aquests esdeveniments poden ser finals, quan el seguiment del pacient s'atura després de l'esdeveniment, o bé intermedis, quan l'individu continua sota observació. La presència d'esdeveniments finals complica l'anàlisi dels intermedis ja que n'impedeix la seva completa observació, induint una possible censura depenent.En aquest context, es requereixen metodologies apropiades. Els següents mètodes són emprats: riscos competitius, models multiestat i riscos semi-competitius. A resultes de l'aplicació de mètodes per riscos competitius i models multi-estat, proposem dues aportacions rellevants al coneixement de la malaltia: (1) la caracterització dels pacients amb un alt risc de progressió com a primer esdeveniment després de la diagnosi, i (2) la construcció d'un model pronòstic dinàmic per al risc de progressió.La situació de riscos competitius es dóna quan volem descriure el temps fins al primer entre K possibles esdeveniments, juntament amb un indicador del tipus d'esdeveniment observat. En l'estudi EPICURO, és rellevant estudiar el temps fins al primer entre recidiva, progressió o mort. La caracterització d'aquest primer esdeveniment permetria seleccionar el millor tractament d'acord amb el perfil de risc basal del pacient.Els models multi-estat descriuen les diferents evolucions que la malaltia pot seguir, establint relacions entre els esdeveniments d'interès: per exemple, un pacient pot experimentar una recidiva del tumor primari, i després morir, o bé pot morir sense haver tingut cap recaiguda de la malaltia. Una característica interessant d'aquests models és que permeten fer prediccions del risc de futurs esdeveniments per a un pacient, d'acord amb la història que hagi pogut tenir fins aquell moment. En el cas de càncer de bufeta podrem avaluar la influència que té en el risc de progressar haver patit o no una recidiva prèvia.Un cas especial de model multi-estat és aquell que conté un esdeveniment intermedi E1, i un esdeveniment final, E2. Siguin T1 i T2 els temps fins aquests esdeveniments, respectivament. Ni l'anàlisi de riscos competitius ni els models multi-estat permeten adreçar l'estudi de la distribució marginal de T1. En efecte, l'anàlisi de riscos competitius tracta amb la distribució del mínim entre els dostemps, T=min(T1,T2), mentre que els models multi-estat es centren en la distribució condicional de T2|T1, és a dir, en com la ocurrència de E1 modifica el risc de E2. En aquest cas, la distribució de T1 no és identificable a partir de les dades observades. La situació abans descrita, on la ocurrència d'un esdeveniment final impedeix l'observació de l'esdeveniment intermedi és coneguda com a riscos semi-competitius (Fine et al., 2001). L'estratègia d'aquests autors passà per assumir un model per a la distribució conjunta (T1, T2), i aleshores recuperar la distribució marginal de T1 derivada d'aquest model.Proposem una nova metodologia per tractar amb riscos semi-competitius quan el temps fins l'esdeveniment intermedi, T1, està censurat en un interval. En molts estudis mèdics longitudinals, la ocurrència de l'esdeveniment d'interès s'avalua en visites periòdiques del pacient, i per tant, T1 és desconegut, però es sap que pertany al interval comprès entre els temps de dues visites consecutives. Els mètodes per riscos semi-competitius en el context usual de censura per la dreta no són vàlids en aquest cas i és necessària una nova aproximació. En aquest treball ampliem la metodología semi-paramètrica proposada per Fine et al. (2001), que assumeix un model de còpula de Clayton (1978) per a descriure la dependència entre T1 i T2. Assumint el mateix model, desenvolupem un algoritme iteratiu que estima conjuntament el paràmetre d'associació del model de còpula, així com la funció de supervivència del temps intermedi T1.Fine, J. P.; Jiang, H. & Chappell, R. (2001), 'On Semi-Competing Risks Data', Biometrika 88(4), 907--919.Clayton, D. G. (1978), 'A Model for Association in Bivariate Life Tables and Its Application in Epidemiological Studies of Familial. Tendency in Chronic Disease Incidence', Biometrika 65(1), 141--151.La presente tesis trata sobre técnicas de análisis de supervivencia en situaciones con múltiples eventos y patrones complejos de censura. Proponemos una nueva metodología para tratar el problema de riesgos semi-competitivos cuando los datos están censurados en un intervalo. La motivación de este trabajo nace de nuestra colaboración con el estudio Español de Cáncer de Vejiga (SBC/EPICURO), el más grande estudio sobre cáncer de vejiga realizado en España hasta el momento. Nuestra participación en el mismo se centra en la modelización e identificación de factores pronósticos en el curso de la enfermedad.El curso de enfermedades complejas tales como el cáncer o la infección por VIH, se caracteriza por la ocurrencia de múltiples eventos en el mismo paciente, como por ejemplo la recaída o la muerte. Estos eventos pueden ser finales, cuando el seguimiento del paciente termina con el evento, o bien intermedios, cuando el individuo sigue bajo observación. La presencia de eventos finales complica el análisis de los eventos intermedios, ya que impiden su completa observación, induciendo una posible censura dependiente.En este contexto, se requieren metodologías apropiadas. Se utilizan los siguientes métodos: riesgos competitivos, modelos multiestado y riesgos semi-competitivos. De la aplicación de métodos para riesgos competitivos y modelos multi-estado resultan dos aportaciones relevantes sobre el conocimiento de la enfermedad: (1) la caracterización de los pacientes con un alto riesgo de progresión como primer evento después del diagnóstico, y (2) la construcción de un modelo pronóstico y dinámico para el riesgo de progresión.El problema de riesgos competitivos aparece cuando queremos describir el tiempo hasta el primero de K posibles eventos, junto con un indicador del tipo de evento observado. En el estudio SBC/EPICURO es relevante estudiar el tiempo hasta el primero entre recidiva, progresión o muerte. La caracterización de este primer evento permitiría seleccionar el tratamiento más adecuado de acuerdo con el perfil de riesgo basal del paciente.Los modelos multi-estado describen las diferentes tipologías que el curso de la enfermedad puede seguir, estableciendo relaciones entre los eventos de interés. Por ejemplo, un paciente puede experimentar una recidiva y después morir, o bien puede morir sin haber tenido recaída alguna. El potencial interesante de los modelos multi-estado es que permiten realizar predicciones sobre el riesgo de futuros eventos dada la historia del paciente hasta ese momento. En el caso del cáncer de vejiga, podremos evaluar la influencia que tiene en el riesgo de progresar el haber tenido o no una recidiva previa.Un caso especial de modelo multi-estado es el que contiene un evento intermedio E1 y uno final, E2. Sean T1 y T2 los tiempos hasta tales eventos, respectivamente. Ni el análisis de riesgos competitivos ni los modelos multi-estado permiten estudiar la distribución marginal de T1. En efecto, el análisis de riesgos competitivos trata con la distribución del mínimo entre los dos tiempos, T=min(T1,T2), mientras que los modelos multi-estado se centran en la distribución condicional de T2 dado T1, T2|T1, en cómo la ocurrencia de E1 modifica el riesgo de E2. En ambos casos, la distribución de T1 no es identificable a partir de los datos observados.La situación anteriormente descrita donde un evento final impide la observación de un evento intermedio se conoce como riesgos semi-competitivos (Fine et al. 2001). La estrategia de estos autores asume un modelo para la distribución conjunta (T1,T2) para así recuperar la distribución de T1 derivada de ese modelo.Proponemos una nueva metodología para tratar con riesgos semi-competitivos cuando el tiempo hasta el evento intermedio, T1, esta censurado en un intervalo. En muchos estudios médicos longitudinales, la ocurrencia del evento de interés se evalúa en visitas periódicas al paciente, por lo que T1 es desconocido, aunque se conoce que pertenece al intervalo comprendido entre los tiempos de dos visitas consecutivas. Los métodos para riesgos semi-competitivos en el contexto usual de censura por la derecha no son válidos en este caso y se requiere una nueva aproximación. En este trabajo ampliamos la metodología semi-paramétrica propuesta por Fine et al. (2001), que asume una cópula de Clayton (1978) para describir la dependencia entre T1 y T2. Bajo el mismo modelo de asociación, desarrollamos un algoritmo iterativo que estima conjuntamente el parámetro de asociación del modelo de cópula, así como la función de supervivencia del tiempo al evento intermedio T1.Fine, J. P.; Jiang, H. & Chappell, R. (2001), 'On Semi-Competing Risks Data', Biometrika 88(4), 907--919. Clayton, D. G. (1978), 'A Model for Association in Bivariate Life Tables and Its Application in Epidemiological Studies of Familial. Tendency in Chronic Disease Incidence', Biometrika 65(1), 141--151

Personalized Hepatobiliary Cancer Treatment

Personalized treatments for biliary tract carcinoma patients could improve the overall outcomes, mainly by withholding treatments from patients who are unlikely to benefit from surgery or chemotherapy. In order to determine the best treatment, at the optimal time in the disease course, in the center with the best outcomes, for each individual patient, large databases have to be utilized to construct appropriate validated models. The works included in this thesis aim to contribute to the development of personalized medicine using accurate prognostication and prediction rules

Surgically treated renal cell carcinoma : Prognostic factors and outcomes of treatment

Background Kidney cancer is the 12th most common malignancy worldwide, accounting for over 400,000 new cases in 2018 (1). As renal cell carcinoma (RCC) incidence and mortality, as well as treatment patterns, vary widely in Europe, to plan strategies for the future, we need to comprehend the current situation in Finland. Accurate prognostic tools are essential for detecting cancers amongst the tumours noted in imaging studies and choosing optimal treatment for cancer patients. The Tumor, Node, Metastasis (TNM) staging system and International Society of Urologic Pathology (ISUP)/Fuhrman grading system are the most commonly used prognostic parameters for RCC. Currently, risk stratification relies on prognostic nomograms or risk stratification tools combining clinical, anatomical and histopathological data. However, these models have well-known limitations. Treatment for RCC is changing. Over the last decades, more incidental RCCs were found, and more minor lesions were operated on using less invasive techniques. At the opposite end of the disease spectrum, selected metastatic RCC patients receive a combined treatment consisting of nephrectomy, metastasectomy and oncologic therapies. Surgery for locally advanced and metastasised tumours must be justified by the prospect of an improved outcome or quality of life. Decisions to operate on metastatic RCCs are currently based on expert opinions and nomograms designed for targeted therapy survival estimations only. Thus, better prognostic markers and diagnostic tools are needed. Aims The aims of this PhD study were to evaluate the current changes in the clinical picture, treatment and outcomes of RCC in Helsinki University Hospital district. Further analysis was done to determine the clinical outcomes of surgically treated RCC with tumour thrombus and metastasised RCC (mRCC). The authors aimed to externally validate the performance of the Leuven-Udine (LU) prognostic group model for mRCC and to evaluate the prognostic value of serum concentration of tumour-associated trypsin inhibitor (TATI). The performance of renal tumour diameter and parenchymal invasion depth was compared with more complex classifications to assess their accuracy in predicting the nephrectomy performed. Patients and methods All patients studied were either suspected to have RCC or had RCC, and the majority of patients underwent nephrectomy at the Helsinki University Hospital (HUH). There were 1,719 patients with tumours suspected of RCC evaluated in four periods from 2006 to 2016 for clinical characteristics and treatments offered. From 2006–2014, 142 RCC patients with tumour thrombus (TT) were operated on at HUH. In total, using computed tomography (CT) or magnetic resonance imaging (MRI) images of 915 patients, tumour maximum diameter, depth of invasion, Preoperative Aspects and Dimensions Used for an Anatomical (PADUA) score and Renal Tumour Invasion Index (RTII) were estimated. There were 97 patients with metastatic RCC undergoing surgery for metastases. Preoperative and postoperative serum levels of tumour associated trypsin inhibitor (S-TATI) of 132 RCC patients were determined by time-resolved immunofluorescence assay in 2006-2010. Main results and conclusions During the study period, the proportions of frail and co-morbid patients increased significantly as did the percentage of small (diameter ≤4 cm) and asymptomatic tumours. The use of surveillance as treatment increased significantly while the use of cytoreductive nephrectomies (CNs) decreased to 54%. However, CN combined with tyrosine kinase inhibitors remained the primary option in patients with metastatic RCC. However, the changing landscape of RCCs has already affected and will increasingly affect the treatments given. For RCC patients with TT, no statistically significant difference in survival was found amongst the different levels of the venous extension. The prognosis for operated RCC patients with TT was good in the absence of papillary histology of primary tumour, lymphoid or distant metastases. Surgery also remains a feasible option for selected patients in the era of modern oncologic therapy. In predicting the type of nephrectomy, partial or radical, the simple measurements of tumour diameter and parenchymal invasion, were superior to the more complex classification. Hence, all of them were significant predictors for nephrectomy type. Our results recommend that potential anatomical classifications should be tested against these user-friendly measurements, diameter and parenchymal invasion. Overall survival (OS) was more favourable for patients undergoing complete metastasectomy than patients with non-complete metastasectomy and time to systemic therapy was longer. Patients with skeletal metastases had shorter survival than patients with other metastatic sites whereas patients with lung metastases had the most favourable prognosis. In this study population, the performance of the LU prognostic group model could not be validated. Despite the abundant amount of inauspicious prognostic factors in our patient cohort, survival rates were reasonable. Significant associations with preoperative S-TATI and Chronic Kidney Disease Stage (CKD grade), tumour stage, lymph-node involvement, metastatic status and preoperative C-reactive protein (CRP) level were noted. S-TATI, as a continuous variable, however, significantly predicted OS and cancer-specific survival (CSS). Prognostic significance of S-TATI should be further studied in larger patient cohorts and prospective settings.Munuaissyöpä on iäkkäiden tauti. Munuaiskasvaimet todetaan tavallisesti muista syistä tehtyjen kuvantamistutkimusten takia. Pelkät kuvantamistutkimukset eivät aina riitä taudin luonteen selvittämiseksi. Paikallisen taudin ensisijainen hoito on munuaisen poisto tai kasvaimen osapoisto, ja taudin ennuste on yleensä hyvä. Laskimoihin kasvaintappina edenneitä munuaissyöpiä pyritään ensisijaisesti hoitamaan leikkaushoidolla. Etäpesäkkeistä tautia hoidetaan lääkehoidolla, mutta voidaan valikoiduissa tapauksissa hoitaa myös emokasvaimen poistolla yhdistettynä tarvittaessa etäpesäkkeiden poistoon. Jotta raskaat kirurgiset toimenpiteet levinneessä taudissa tai muuten hauraille potilaille voidaan perustella, tulee olla selvää näyttöä hyödystä joko elinaikalisänä tai parantuneena elämänlaatuna ja oman alueen kirurgiset tulokset ja komplikaatiomäärät tulee tietää. Väitöskirjatutkimus tehtiin Helsingin yliopistosairaalassa leikatuista tai seuratuista potilaista, joilla oli munuaissyöväksi epäilty kasvain tai munuaissyöpä. Potilaita oli 1719, ja heitä oli hoidettu ja seurattu vuosina 2006-2016. Aineistossamme vuosien 2006-2016 välillä selvästi sairaampien ja vanhempien potilaiden sekä pienten todettujen munuaiskasvainten osuudet kasvoivat merkittävästi. Seuranta hoitomuotona lisääntyi, kun taas emokasvainten poistojen määrä etäpesäkkeisessä taudissa väheni. Potilaiden, joilla oli laskimotapillisten munuaissyöpä, ennuste leikkaushoidon jälkeen oli suotuisa. Tosin emokasvaimen papillaarinen histologia ja levinneisyys imusolmukkeisiin tai kauemmas huononsivat leikatun potilaan ennustetta. Täydellinen etäpesäkkeen ja emokasvaimen poisto pidensi eloonjäämisaikaa ja siirsi munuaissyövän lääkehoidon aloitusta pidemmälle verrattuna leikkaukseen, jossa ei saatu kaikkea syöpämateriaalia poistettua, levinnyttä munuaissyöpää sairastavilla potilailla. Keuhkoetäpesäkkeisillä potilailla oli paras ennuste, ja luustoetäpesäkkeisillä huonoin. Yksinkertaiset anatomiset mitat, kasvaimen halkaisija ja kasvusyvyys, ennustivat monimutkaisempia luokituksia paremmin, tehtiinkö paikallisen munuaiskasvaimen hoidoksi munuaisen kokopoisto vai osapoisto. Leikkauksen jälkeen mitattuna seerumin TATI -merkkiaine ennusti kokonaiskuolleisuutta ja syöpäkuolleisuutta aineistomme munuaissyöpäpotilailla. Todellisen ennusteellisen merkityksen selvittämiseksi S-TATIa pitäisi tutkia suuremmassa aineistossa etenevässä tutkimusasetelmassa. Lisää työkaluja kaivataan sekä syöpien löytämiseksi hyvänlaatuisten munuaismuutosten joukosta että valitsemaan oikeat potilaat oikeisiin hoitoihin tai seurantaan ja määrittelemään seurannan tiheyden. Kun entistä vanhemmilla, hauraammilla ja sairaammilla potilailla löytyy aiempaa pienempiä kasvaimia, tulee hoidon hyötyjä ja haittoja punnita tarkasti. Tällä hetkellä syöpäkuoleman ja uusiutumisen riskiä ennustetaan munuaiskasvaimen anatomiasta, histologiasta sekä kliinisistä tiedoista koostetuilla pisteytysjärjestelmillä. Tarkempia ennusteellisia biomarkkereita etsitään kuumeisesti. Parhaat merkkiaineet olisivat esimerkiksi verestä tai virtsasta mitattavia, jotta kajoavia toimenpiteitä ei tarvittaisi –toistaiseksi yhtään tarkkaa ja kliiniseen tai tutkimuskäyttöön sopivaa merkkiainetta ei ole onnistuttu löytämään

APPROPRIATE USE AND VALUE OF SURVEILLANCE AMONG MEDICARE PATIENTS WITH NON-MUSCLE-INVASIVE BLADDER CANCER

Bladder cancer patients have the highest median age at diagnosis of 73 years compared with all other cancer types and often live with substantial disease and comorbidity burden. Due to high recurrence rates, intensive surveillance strategies, and expensive therapies, bladder cancer has the highest lifetime costs per patient from diagnosis to death. Regular surveillance cystoscopy is recommended for patients with non-muscle invasive bladder cancer (NMIBC) of all ages to detect potential recurrences, despite a lack of large randomized controlled trials examining how the use of cystoscopy affects patient outcomes. The overall objectives of this dissertation were (1) to investigate factors associated with receipt of surveillance cystoscopy; (2) to characterize survival outcomes of NMIBC patients undergoing surveillance; and (3) to examine the cost-effectiveness of three different risk-stratified and uniform surveillance recommendations. We used the Surveillance Epidemiology and End Results (SEER)-Medicare data from 2000 to 2014 to assess disease characteristics and outcomes. We also developed a patient-level simulation model to quantify the health-economic impact of different frequencies of surveillance over five years. In Aim 1, we found that NMIBC patients aged ≥85 years, those with poor disability status, and those having ≥3 comorbidities at diagnosis were least likely to undergo recommended (≥7 cystoscopies) or low-intensity (≥4 cystoscopies) surveillance over the first two years post-diagnosis. As the age at diagnosis and the number of comorbid conditions increased, the odds of receiving recommended cystoscopy frequency as well as the rate of cystoscopy decreased. In Aim 2, older patients (≥75 vs. 66-74 years) and those with poor disability status at diagnosis had higher cumulative incidence of both bladder-cancer and other-cause death, regardless of frequency of cystoscopy. In Aim 3, low-intensity risk-stratified surveillance, with cystoscopy frequency increasing progressively with risk, was associated with different trade-offs such as lower costs and fewer false positive cases per patient, compared with a more frequent high-intensity risk-stratified approach and uniform surveillance. This research highlights the importance of age, comorbidities, functional status, and risk-stratification on receipt of surveillance and outcomes of NMIBC patients. Additionally, findings from our study suggest intermediate-risk patients may benefit from less frequent surveillance than high-risk patients.Doctor of Philosoph