Alzheimer's disease (AD) is neurodegenerative disorder that causes memory loss and cognitive dysfunction. It affects one in five people over the age of 80 and is distressing for both sufferers and their families. A transitional stage between normal ageing and dementia including AD is termed a mild cognitive impairment (MCI). Recent studies have shown that people with MCI may convert to AD over time although not all MCI cases progress to AD. Much research is now focussing on early detection of AD and diagnosing an MCI that will progress to AD to allow prompt treatment and disease management before the neurons degenerate to a stage beyond repair. Hence, the ability to obtain a method of identifying MCI is of great importance. Virtual reality plays an important role in healthcare and offers opportunities for detection of MCI. There are various studies that have focused on detection of early AD using virtual environments, although results remain limited. One significant drawback of these studies has been their limited capacity to incorporate levels of difficulty to challenge users' capability. Furthermore, at best, these studies have only been able to discriminate between early AD and healthy elderly with about 80% of overall accuracy. As a result, a novel virtual simulation called Virtual Reality for Early Detection of Alzheimer's Disease (VREAD) was developed. VREAD is a quick, easy and friendly tool that aims to investigate cognitive functioning in a group of healthy elderly participants and those with MCI. It focuses on the task of following a route, since Topographical Disorientation (TD) is common in AD. An investigation was set up with two cohorts: non-elderly and elderly participants. The findings with regard to the non-elderly are important as they represent a first step towards implementation with elderly people. The results with elderly participants indicate that this simulation based assessment could provide a method for the detection of MCI since significant correlations between the virtual simulation and existing neuropsychological tests were found. In addition, the results proved that VREAD is comparable with well-known neuropsychological tests, such as Cambridge Neuropsychological Automated Test Battery, Paired Associate Learning (CANTAB PAL) and Graded Naming Test (GNT). Furthermore, analysis through the use of machine learning techniques with regard to the prediction of MCI also obtained encouraging results. This novel simulation was able to predict with about 90% overall accuracy using weighting function proposed to discriminate between MCI and healthy elderly. / Ministry of Higher Education, Malaysia and University Sultan Zainal Abidin, Malaysia (UNisZa)

Krebs entsteht durch das Zusammenspiel von Keimbahn- und somatischen Mutationen sowie Umweltfaktoren. Für Fortschritte in Prävention, Früherkennung und Behandlung von Krebs ist es essenziell die phänotypischen Folgen dieser Mutationen und die Rolle von Umweltfaktoren bei der Steigerung des Krebsrisikos zu verstehen. In dieser Arbeit untersuche ich zunächst die Auswirkungen von Mutationen in einfachen Sequenzwiederholungsregionen (SSRs) auf das Zellwachstum in einem Hefemodell. In einem Mutationsakkumulationsexperiment in Stämmen mit defektem Mismatch-Reparatursystem zeige ich, dass die Störung von MutSβ zu einer erhöhten SSR-Mutationsrate führt, insbesondere bei SSR-Loci die länger als 8 bp sind. Meine Ergebnisse legen nahe, dass MutSβ hauptsächlich für die Reparatur an längeren Repeat-Loci verantwortlich ist. Schließlich zeige ich, dass SSR-Mutationen meist geringfügige, negative Auswirkungen auf das Zellwachstum haben. Als Nächstes untersuche ich die Auswirkungen von Zigarettenrauch auf das Transkriptom von zugänglichem Atemwegsgewebe am Beispiel des Nasenepithels von gesunden Freiwilligen und Patienten mit Verdacht auf oder diagnostiziertem Lungenkrebs. Ich stelle fest, dass Gene und biologische Funktionen, die durch das Rauchen beeinträchtigt werden, bei Patienten langsamer auf ein gesundes Ausgangsniveau zurückkehren. Zudem zeige ich, dass Patienten durch anhaltende, Rauch-assoziierte Immunveränderungen gekennzeichnet sind. Schließlich präsentiere ich einen innovativen Lungenkrebs-Klassifikator, der durch die Berücksichtigung der nasalen Genexpression von Rauch-assoziierten Genen eindeutig bessere Ergebnisse erzielt als ein Modell, das ausschließlich auf klinischen Informationen basiert. Damit belege ich das Potenzial der Genexpression des Nasenepithels zur Verbesserung der Risikostratifizierung auf Bevölkerungsebene anhand eines nicht-invasiven Tests. / Cancer is initiated and sustained by the interplay of germline and somatic mutations and environmental factors. Understanding the phenotypic consequences of mutations and the role of environmental factors in increasing cancer risk is key to improving cancer prevention, early detection, and treatment. In this thesis, I first take advantage of a yeast model to investigate the effects of mutations in simple sequence repeat regions (SSRs) on cell growth. I describe a mutation accumulation experiment conducted in strains with a deletion of the MutSβ gene, a component of the mismatch repair system (MMR). I show that abrogating MutSβ function leads to an increased SSR mutation rate, with a bias towards deletions. I also report a drastic increase in mutation rate in SSR loci longer that 8-bp, suggesting MutSβ is primarily responsible for repair at longer repeat loci. Finally, I show that many SSR mutations have small deleterious effects on cell growth. Next, I investigate the effects of cigarette smoke on the transcriptome of an accessible airway tissue, nasal epithelium, in a cohort of healthy volunteers and patients with suspected or diagnosed lung cancer. I find that smoke injury response is strikingly different in healthy individuals and clinic patients, with genes and biological functions affected by smoking showing a slower reversal to healthy baseline level in clinic patients. I find persistent smoking-associated immune alterations to be a hallmark of the clinic patients. Finally, I show that a lung cancer classifier including nasal expression of smoke-injury-associated genes performs better than a model based exclusively on clinical information, providing evidence for the potential of nasal epithelial gene expression to improve population-level risk stratification with the use of a non-invasive test.

No / Triple negative breast cancers (TNBC) are clinically heterogeneous, an aggressive subtype with poor diagnosis and strong resistance to therapy. There is a need to identify novel robust biomarkers with high specificity for early detection and therapeutic intervention. Microarray gene expression-based studies have offered significant advances in molecular classification and identification of diagnostic/prognostic signatures, however sample scarcity and cohort heterogeneity remains area of concern. In this study, we performed integrated analysis on independent microarray big data studies and identified a robust 880-gene signature for TNBC diagnosis. We further identified 16-gene (OGN, ESR1, GPC3, LHFP, AGR3, LPAR1, LRRC17, TCEAL1, CIRBP, NTN4, TUBA1C, TMSB10, RPL27, RPS3A, RPS18, and NOSTRIN) that are associated to TNBC tissues. The 880-gene signature achieved excellent classification accuracy ratio on each independent expression data sets with overall average of 99.06%, is an indication of its diagnostic power. Gene ontology enrichment analysis of 880-gene signature shows that cell-cycle pathways/processes are important clinical targets for triple negative breast cancer. Further verification of 880-gene signature could provide additive knowledge for better understanding and future direction of triple negative breast cancer research.

Yes / Purpose: We present a subjective approach to detecting glaucomatous defects in enface images and assess its diagnostic performance. We also test the hypothesis that if reflectivity changes precede thickness changes in glaucoma there should be reduced correlation between the modalities in glaucoma compared to controls. Methods: Twenty glaucoma participants and 20 age-matched controls underwent high-resolution OCT scans of one eye. 4 μm-thick enface slabs were constructed through the retina. Enface indices were depths of first gap in visible retinal nerve fiber bundles (RNFBs) and last visible bundle, subjectively evaluated in six sectors of a 3.5 mm circle around the optic disc. Retinal nerve fiber layer thickness (RNFLT) along the same circle was extracted at angles corresponding to enface indices. Between-group differences were tested by linear mixed models. Diagnostic performance was measured by partial receiver operating characteristic area (pAUC). Results: First gap and last visible bundle were closer to the inner limiting membrane in glaucoma eyes (both P < 0.0001). Enface indices showed excellent diagnostic perfor mance (pAUCs 0.63–1.00), similar to RNFLT (pAUCs 0.63–0.95). Correlation between enface and RNFLT parameters was strong in healthy (r = 0.81–0.92) and glaucoma eyes (r = 0.73–0.80). Conclusions: This simple subjective method reliably identifies glaucomatous defects in enface images with diagnostic performance at least as good as existing thickness indices. Thickness and reflectivity were similarly related in healthy and glaucoma eyes, providing no strong evidence of reflectivity loss preceding thinning. Objective analyses may realize further potential of enface OCT images in glaucoma. Translational Relevance: Novel enface OCT indices may aid glaucoma diagnosis.

Yes / Access to the large web content hosted all over the world by users of the Internet engage many hosts, routers/switches and faster links. They challenge the internet backbone to operate at its capacity to assure e±cient content access. This may result in congestion and raises concerns over various Quality of Service (QoS) issues like high delays, high packet loss and low throughput of the system for various Internet applications. Thus, there is a need to develop effective congestion control mechanisms in order to meet various Quality of Service (QoS) related performance parameters. In this paper, our emphasis is on the Active Queue Management (AQM) mechanisms, particularly Random Early Detection (RED). We propose a threshold based novel analytical model based on standard RED mechanism. Various numerical examples are presented for Internet traffic scenarios containing both the burstiness and correlation properties of the network traffic.

Background: Bipolar disorders belong to the most severe mental illnesses, characterized by recurrent depressive and (hypo-)manic episodes and an often chronic disease trajectory. Anecdotal data about famous creative individuals suggest a link between creativity and bipolar disorders (BD). To this day, only a few studies assessed persons at risk for BD and included creativity measures. Objective: This study aimed to further explore and understand the relationship between BD and creativity. For this purpose, we investigated the impact of creativity on a change in symptom severity in at-risk adolescents and young adults. This was defined as the transition to manifest BD and the initial prescription of a mood-stabilizing drug. Methods: The data were obtained from Early-BipoLife, a multicentered, prospective-longitudinal naturalistic cohort study conducted between 2015 and 2018. The participants aged between 15 and 35 were assessed five times over two years or longer. The adolescents and young adults were included in the study when they were screened positive for at least one of the potential risk factors for BD. After the exclusion of 150 participants due to incomplete early detection or creativity measures, the final sample included 1,105 at-risk individuals. The included participants were divided into four different groups, depending on their risk status according to the EPIbipolar and their scores in two creativity measures, the BWAS and the CAQ, respectively (G1: ↓ risk, ↓ creativity; G2: ↓ risk, ↑ creativity; G3: ↑ risk, ↓ creativity; G4: ↑ risk, ↑ creativity). Overall, 25 transitioned into manifest BD and 51 transitioned and/or received initial mood-stabilizing treatment. After the characterization of sociodemographic and clinical characteristics of the sample, the potential impact of creativity on the risk of transitioning to manifest BD and/or the initial prescription of a mood stabilizer was examined. For this, Odds Ratios (OR) and the corresponding 95% confidence intervals were calculated (G2, G3, G4 vs. G 1 as well as G4 vs. G3). This was done twice, one time using the BWAS and the other the CAQ as the creativity measure. Results: When comparing G2 vs. G1 using the EPIbipolar and the BWAS, no significant difference in the risk for transition to manifest BD and/or the initial prescription of a mood-stabilizing drug could be observed. The comparison of G3 vs. G1 revealed a significantly higher risk for transition to BD in G3 (OR = 4.56, 96% CI: 1.13 - 18.46, p = .029). In line with that are the results of the comparison of G4 vs. G1, revealing that the risk was even seven times higher for participants of G4 (OR = 7.05, 95% CI: 1.94 - 25.56, p = .001). Similar results could be observed when comparing G3 vs. G1 (OR = 2.31, CI: 1.02-5.26, p = .041) and G4 vs. G1 (OR = 2.92, CI: 1.38-6.19, p = .004) regarding the second outcome, transitions to manifest BD and/or the initial prescription of a mood stabilizer. The comparison of G4 vs. G3 revealed no significant differences in the risk of transition to BD and/or the initial prescription of a mood-stabilizing agent. The results were confirmed when repeating the analyses using the EPIbipolar and the CAQ, the second creativity measure. Conclusions: The longitudinal design enabled the present analysis to investigate the link between creativity and actual transitions into the manifest disease, making this the first study of this kind. The results suggest that creativity has a significant impact on the risk of developing BD in connection with other risk factors. Furthermore, it speaks in favor of the results, that there were no significant differences despite the very different ways the BWAS and the CAQ assess creativity. Therefore, creativity should be considered in risk evaluations of help-seeking young adults, as it usually presents itself much earlier than other clinical risk factors. Additionally, it is commonly experienced as a resource or positive sense of identity and might be reported more easily by affected individuals. Creativity should also be considered when it comes to the treatment of at-risk states or manifest BD. Knowledge about creative potential could be used in the diagnostic and therapeutic process and further improve compliance regarding psychological and pharmacological therapeutic interventions. For example, creative persons affected by BD might benefit from therapeutic options such as art or music therapy in addition to pharmaco- and psychotherapy. This is highly relevant because effective early interventions can possibly reduce negative consequences such as higher suicidality or psychosocial burden. Still, many aspects of the association between creativity, BD, and risk states remain unknown and need further research. Future studies should repeat the analysis, also implementing longitudinal designs, using different risk or creativity instruments as well as other statistical methods with the aim of investigating associations of creativity with other risk factors. The results showed that creativity cannot be used isolated to assess the risk status of help-seeking adolescents at this point. Therefore, it should not be pathologized but rather be viewed as a resource that can and should be integrated and considered when assessing and treating individuals at risk or with manifest BD.:List of Abbreviations List of Figures List of Tables Abstract German Abstract 1. Introduction 2. Theoretical Background 2.1 Early detection of bipolar disorders 2.1.1 Prodromal or risk state for bipolar disorders 2.1.2 Risk factors (according to EPIbipolar) and risk assessment tools 2.2 Creativity in association with bipolar disorders 2.2.1 Definitions of creativity 2.2.2 Measuring creativity 2.2.3 Investigation of the association between creativity and bipolar disorders 2.2.4 Creativity in persons at risk for bipolar disorders 2.3 Objectives and research questions 3. Methods 3.1 Sample 3.1.1 Overview of the sample 3.1.2 Comparison of excluded and included participants 3.2 Procedures 3.2.1 Quality assurance 3.2.2 Baseline assessment 3.2.3 Follow-up assessments 3.3 Measures 3.3.1 Structured Clinical Interview for DSM-IV Disorders (SCID) 3.3.2 Early Phase Inventory for Bipolar Disorders (EPIbipolar) 3.3.3 Barron-Welsh Art Scale (BWAS) 3.3.4 Creative Achievement Questionnaire (CAQ) 3.4 Group classification procedure and outcomes 3.4.1 Group classification procedure 3.4.2 Outcomes 3.5 Statistical analysis 4. Results 4.1 Descriptive Statistics 4.1.1 Comparison of sociodemographic characteristics between the study groups 4.2 Research Question 1: The impact of creativity on the transition to BD and/or the initial prescription of a mood stabilizer in study groups 1-4 4.2.1 Results for groups 2-4 versus 1 with the BWAS as a creativity measure 4.2.2 Results for groups 2-4 versus 1 with the CAQ as a creativity measure 4.3 Research Question 2: The impact of creativity on the transition to BD and/or the initial prescription of a mood stabilizer in study groups 3 and 4 4.3.1 Results for groups 4 versus 3 with the BWAS as a creativity measure 4.3.2 Results for groups 4 versus 3 with the CAQ as a creativity measure 5. Discussion 5.1 Summary and integration of findings 5.1.1 Comparison of sociodemographic characteristics between the study groups 5.1.2 Research Question 1: The impact of creativity on the transition to BD and/or the initial prescription of a mood stabilizer in two study groups 5.1.3 Research Question 2: The impact of creativity on the transition to BD and/or the initial prescription of a mood stabilizer in two study groups 5.2 Strengths and limitations 5.3 Implications for future research and practice 5.4 Conclusion 6. References Appendix / Hintergrund: Bipolare Störungen gehören zu den schwersten psychischen Erkrankungen, die durch wiederkehrende depressive und (hypo-)manische Episoden sowie meist chronische Krankheitsverläufe gekennzeichnet sind. Anekdotische Daten über berühmte kreative Persönlichkeiten lassen eine Verbindung zwischen Kreativität und bipolaren Störungen (BS) vermuten. Bisher wurden nur wenige Studien durchgeführt, die Personen mit einem erhöhten Risiko für BS untersuchen und dabei ihre Kreativität mit einbezogen haben. Fragestellung: Ziel dieser Studie war es, den möglichen Zusammenhang zwischen BS und Kreativität besser zu verstehen. Hierzu untersuchten wir den Einfluss von Kreativität auf das Risiko einer Symptomverschlechterung bei Jugendlichen und jungen Erwachsenen die bereits gewisse Risikofaktoren für BS erfüllten. Diese Verschlechterung wurde definiert als der Übergang in eine manifeste BS oder die erstmalige Verschreibung eines stimmungsstabilisierenden Medikaments. Methoden: Die verwendeten Daten wurden in der multizentrischen, prospektiven und longitudinalen Kohortenstudie Early-BipoLife erhoben, die zwischen 2015 und 2018 durchgeführt wurde. Die Teilnehmenden im Alter zwischen 15 und 35 Jahren wurden fünfmal über einen Zeitraum von mindestens zwei Jahren untersucht. Die Jugendlichen und jungen Erwachsenen wurden in die Studie aufgenommen, wenn sie beim Erstkontakt mindestens einen potenziellen Risikofaktor für BS erfüllten. Nach dem Ausschluss von 150 Teilnehmenden aufgrund unvollständiger Früherkennungs- oder Kreativitätsfragebögen, umfasste die endgültige Stichprobe 1,105 Personen. Die eingeschlossenen Teilnehmenden wurden abhängig von ihrem Risikostatus gemäß des EPIbipolars sowie ihren Ergebnissen in zwei Kreativitätstests, dem BWAS und dem CAQ, in vier Gruppen eingeteilt (G1: ↓ Risiko, ↓ Kreativität; G2: ↓ Risiko, ↑ Kreativität; G3: ↑ Risiko, ↓ Kreativität; G4: ↑ Risiko, ↑ Kreativität). Insgesamt entwickelten 25 Proband:innen eine manifeste BS und 51 erhielten die Diagnose und/oder eine initiale stimmungsstabilisierende Behandlung. Nach der Charakterisierung der soziodemografischen und klinischen Stichprobenmerkmale wurde der potenzielle Einfluss von Kreativität auf das Risiko der Manifestation einer BS und/oder des erstmaligen Verschreibens eines Stimmungsstabilisierers untersucht. Hierfür wurden Odds Ratios (OR) und die entsprechenden 95%-Konfidenzintervalle bestimmt (G2, G3, G4 vs. G1 sowie G4 vs. G3). Alle Analysen wurden zwei Mal durchgeführt, einmal unter Verwendung des BWAS und das andere Mal unter Verwendung des CAQ als Kreativitätsinstrument. Ergebnisse: Beim Vergleich von G2 mit G1 unter Verwendung des EPIbipolars und des BWAS konnte kein signifikanter Unterschied bezüglich des Risikos für den Übergang in eine manifeste BS und/oder der initialen Verschreibung eines Stimmungsstabilisierers beobachtet werden. Der Vergleich von G3 mit G1 offenbarte ein signifikant höheres Risiko für den Übergang zu BS in G3 (OR = 4.56, 96% CI: 1.13 - 18.46, p = .029). Im Einklang damit stehen die Ergebnisse des Vergleichs von G4 mit G1, die zeigten, dass das Risiko für Proband:innen in G4 sogar siebenmal höher war (OR = 7.05, 95% CI: 1.94 - 25.56, p = .001). Ähnliche Ergebnisse konnten hinsichtlich des Übergangs zur manifesten Störung und/oder der erstmaligen Verschreibung eines stimmungsstabilisierenden Medikaments beim Vergleich von G3 vs. G1 (OR = 2.31, CI: 1.02-5.26, p = .041) und G4 vs. G1 (OR = 2.92, CI: 1.38-6.19, p = .004) beobachtet werden. Beim Vergleich von G4 mit G3 zeigten sich keine signifikanten Unterschiede bezüglich des Risikos. Die vorangegangenen Ergebnisse konnten mit der Wiederholung der Analysen unter Verwendung des Epibipolars und des CAQ, dem zweiten Kreativitätsmaß, bestätigt werden. Schlussfolgerungen: Das longitudinale Studiendesign ermöglichte es, den Zusammenhang zwischen Kreativität und tatsächlichen Übergängen in manifeste BS zu untersuchen, was diese Studie zur Ersten ihrer Art macht. Die Ergebnisse deuten darauf hin, dass Kreativität einen signifikanten Einfluss auf das Risiko der Entwicklung von BS hat. Darüber hinaus spricht es für die Ergebnisse, dass es trotz der sehr unterschiedlichen Kreativitätsaspekte, die die BWAS und CAQ erfassen, keine signifikanten Unterschiede zwischen den Analysen gab. Die Studienergebnisse legen nahe, dass Kreativität als ein Teil des Früherkennungsprozesses für BS berücksichtigt werden sollte und gleichzeitig bedeutend früher gemessen werden kann als andere klinische Risikofaktoren. Hinzu kommt, dass Kreativität häufig als Ressource oder positive Identität wahrgenommen wird und somit möglicherweise leichter von den Betroffenen berichtet wird. Des Weiteren sollte Kreativität bei der Behandlung von Hilfesuchenden berücksichtigt werden, da Kenntnisse über kreative Potenziale im diagnostischen und therapeutischen Prozess genutzt und die Compliance in Bezug auf psychotherapeutische und pharmakologische Interventionen verbessert werden könnte. Beispielsweise könnten kreative Personen, die von BS betroffen sind, von ergänzenden therapeutischen Methoden wie Kunst- oder Musiktherapie profitieren. Dies ist von hoher Relevanz, da effektive Frühinterventionen möglicherweise negative Konsequenzen wie Suizidalität und psychosoziale Belastung reduzieren können. Dennoch bleiben viele Aspekte der Assoziation zwischen Kreativität, BS und Risikofaktoren ungeklärt und bedürfen weiterer Forschung. Zukünftige Längsschnittstudien sollten unter Verwendung weiterer Risiko- und Kreativitätsinstrumente sowie anderen statistischen Methoden, die komplexere Zusammenhänge abbilden können, die Analyse wiederholen. Die Studienergebnisse zeigten, dass Kreativität allein zum jetzigen Zeitpunkt nicht verwendet werden kann, um den Risikostatus von Hilfesuchenden zu beurteilen. Daher sollte sie nicht pathologisiert, sondern eher als eine Ressource betrachtet werden, die bei der Beurteilung und Behandlung von Risikopersonen integriert und berücksichtigt werden kann und sollte.:List of Abbreviations List of Figures List of Tables Abstract German Abstract 1. Introduction 2. Theoretical Background 2.1 Early detection of bipolar disorders 2.1.1 Prodromal or risk state for bipolar disorders 2.1.2 Risk factors (according to EPIbipolar) and risk assessment tools 2.2 Creativity in association with bipolar disorders 2.2.1 Definitions of creativity 2.2.2 Measuring creativity 2.2.3 Investigation of the association between creativity and bipolar disorders 2.2.4 Creativity in persons at risk for bipolar disorders 2.3 Objectives and research questions 3. Methods 3.1 Sample 3.1.1 Overview of the sample 3.1.2 Comparison of excluded and included participants 3.2 Procedures 3.2.1 Quality assurance 3.2.2 Baseline assessment 3.2.3 Follow-up assessments 3.3 Measures 3.3.1 Structured Clinical Interview for DSM-IV Disorders (SCID) 3.3.2 Early Phase Inventory for Bipolar Disorders (EPIbipolar) 3.3.3 Barron-Welsh Art Scale (BWAS) 3.3.4 Creative Achievement Questionnaire (CAQ) 3.4 Group classification procedure and outcomes 3.4.1 Group classification procedure 3.4.2 Outcomes 3.5 Statistical analysis 4. Results 4.1 Descriptive Statistics 4.1.1 Comparison of sociodemographic characteristics between the study groups 4.2 Research Question 1: The impact of creativity on the transition to BD and/or the initial prescription of a mood stabilizer in study groups 1-4 4.2.1 Results for groups 2-4 versus 1 with the BWAS as a creativity measure 4.2.2 Results for groups 2-4 versus 1 with the CAQ as a creativity measure 4.3 Research Question 2: The impact of creativity on the transition to BD and/or the initial prescription of a mood stabilizer in study groups 3 and 4 4.3.1 Results for groups 4 versus 3 with the BWAS as a creativity measure 4.3.2 Results for groups 4 versus 3 with the CAQ as a creativity measure 5. Discussion 5.1 Summary and integration of findings 5.1.1 Comparison of sociodemographic characteristics between the study groups 5.1.2 Research Question 1: The impact of creativity on the transition to BD and/or the initial prescription of a mood stabilizer in two study groups 5.1.3 Research Question 2: The impact of creativity on the transition to BD and/or the initial prescription of a mood stabilizer in two study groups 5.2 Strengths and limitations 5.3 Implications for future research and practice 5.4 Conclusion 6. References Appendix

研究背景： / 2009年起，中國政府發起並資助了一項覆蓋全國31個省221個鄉村、針對100萬名農村婦女的細胞學及肉眼觀察宮頸癌篩查試點項目。國家及地方政府需要對可行的篩查策略進行衛生經濟學評估，為下一步擴大規模的篩查提供政策依據。 / 研究目標： / 應用人群特異性Markov模型，對巴氏塗片及肉眼觀察的宮頸癌篩查策略進行成本效果及成本效用兩方面的衛生經濟學評估，進而為中國農村婦女宮頸癌篩查政策的制定提供依據。 / 研究方法： / 本論文工作建立了Markov人群動態擬合模型，該模型能夠整合與中國農村宮頸癌流行情況相吻合的成本及健康狀況的數據，進而用於擬合20年內35-59歲中國農村婦女在有/無篩查幹預下的成本、效用和效果。本文分析的八個備選篩查策略包括：採用醋酸染色肉眼觀察（VIA）或傳統細胞學（巴氏塗片）分別進行10年，5年，3年及1年一次的篩查。 / 本文從社會學角度出發，成本數據涵蓋篩查、診斷及治療過程中產生的直接及間接成本。模型在結構上綜合了已被廣泛認可的宮頸癌自然發展史模型，以及宮頸癌及其癌前病變（CIN）在中國農村進行篩查和治療的標準臨床路徑。模型輸入參數盡可能地使用了能夠反映中國農村婦女人群特異性的數據。通過對比國家報告數據與模型預測結果，本文從全死因死亡率、宮頸癌死亡率及宮頸癌發病率三個方面驗證了模型的可信度。 / 模型的結局變量包括：累計成本、累計生命年(LYs)、累計質量調整生命年(QALYs)、預期宮頸癌死亡率及發病率降低百分比(%)、CIN 相對風險、宮頸浸潤癌相對風險，增量成本效用比(ICUR, 表述為每挽救一個質量調整生命年消耗的成本)及增量成本效果比(ICER, 表述為每挽救一個生命年消耗的成本)等。與無篩查幹預相比，我們界定ICUR及ICER小於三倍人均國內生產總值（76,824元，2009年)的優勢策略為‘具有成本效益’的選擇，並將其中ICUR和ICER最低的策略，定義為‘最具成本效益’的策略，將具有最大健康效益的策略（挽救最多質量調整生命年或生命年的策略），定義為‘最有效’的策略。同時，我們對可能影響決策的不確定因素進行了敏感性分析。 / 結果： / 與無篩查幹預相比，肉眼觀察及巴氏塗片篩查均能夠減少宮頸癌患病例數，進而顯示出一定的健康效益。較短的篩查間隔具有更高的健康效益。模型預測在不同的篩查策略幹預下，宮頸癌死亡率和發病率分別有望降低6.67-31.95%和5.12-24.71%，預期CIN發病相對風險為0.89-0.98，預期宮頸癌發病相對風險為0.73-0.95。篩查幹預對健康的保護作用在本研究中得到了證實。 / 成本效用分析顯示，10年一次的肉眼觀察策略最具成本效益，其次為5年一次、3年一次、1年一次的肉眼觀察篩查策略及1年一次的巴氏塗片篩查策略。與無篩查幹預相比，如上策略每挽救一個質量調整生命年消耗的成本為11,921至26,069元（1,892-4,138美元，2012年）。同時成本效果分析也顯示，10年一次的肉眼觀察策略最具成本效益，其次為5年一次的肉眼觀察策略及5年一次的巴氏塗片篩查策略。同樣與無篩查幹預相比，如上策略每挽救一個生命年消耗的成本為37,211至68,226元（5,906-18,830美元，2012年）。 / 對於某一既定策略，相應的ICUR和ICER受當地經濟狀況相關因素的影響最大，這些因素包括治療成本、篩查成本和成本貼現率。從檢測技術水平上看，肉眼觀察對分析結果的影響小於巴氏塗片，原因是前者敏感度範圍較小。篩查覆蓋率、初篩陽性隨訪率、診斷陽性治療率也都與相應的ICUR和ICER呈負相關性。敏感性分析結果顯示本文中模型對於健康結局的預測，及相關的衛生經濟學分析，受自然史模型中HPV感染和CIN之間轉移概率的不確定性的影響最大。HPV感染與CIN間的進展和逆轉概率是該項模型研究的核心參數。 / 結論： / 本文中成本效用和成本效果分析均顯示，相較於傳統的細胞學篩查策略，採用間隔時間較長（10年或5年）的肉眼觀察篩查策略，對一般發病地區的35-59歲的農村婦女來說，是更具‘成本效益’的選擇。對於宮頸癌高發地區，其篩查頻率可以提高到1年一次。1年一次的巴氏塗片篩查策略，是最有效的篩查策略，可以挽救最多的生命。但採用該策略時，應在財政預算允許的前提下，確保篩查技術和項目完成的質量。 / 篩查項目的高覆蓋率，對篩查陽性患者良好的隨訪和診治，初篩檢測技術平均水平以上的表現，以及較低的篩查和治療成本是確保篩查項目具備成本效益優勢的核心因素。本文完成的成本效用及成本效果分析，能夠為公共衛生決策提供重要的輔助作用。 / Background: / A Chinese government-sponsored cytology/visual inspection pilot cervical cancer screening program covered 10 million rural women in 221 counties of 31 provinces was initiated in 2009. Both the local and national governments in China need health economic evaluations of feasible strategies so as to make better policies for the next-step enlarging screening. / Objectives: / To perform health economic evaluations of Pap smear and visual inspection cervical cancer screening strategies using population-specific Markov modeling cost-utility (CUA) and cost-effectiveness (CEA) analyses, in order to assist screening policy making for women in rural China. / Methods: / Markov simulation models were developed to synthesize the evidence on costs and health outcomes related to cervical cancer epidemiology in rural China, and applied to predict the long-term utility, effectiveness and costs for hypothetical cohorts of 35-59 years old rural Chinese women, with or without the presence of screening over 20 years. The eight alternative screening strategies assessed were visual inspection with acetic acid (VIA) or traditional cytology (Pap smear) each with ten-year, five-year, three-year and one year screening intervals. / The study was conducted from the societal perspective, thus both directed and non-direct costs related to screening, diagnosis and treatment interventions were considered. The model structures incorporated with the well-accepted the natural history model of cervical cancer and the standard clinical pathway of screening and treatment interventions for precancerous lesions (CIN) and cervical cancer in real practice in rural China. Population-specific data were used as much as possible to be the model inputs. The model estimates were validated by comparison of our predictions of all-cause mortality, cervical cancer mortality and cervical cancer incidence with the national reported data. / Outcome variables included cumulative cost, life years (LYs), quality-adjusted life years (QALYs), predicted reduction(%) in cervical cancer mortality and incidence, relative risk of CIN, relative risk of cervical cancer, incremental cost-utility ratio (ICUR, presented as cost per QALY saved) and incremental cost-effectiveness ratio (ICER, presented as cost per life year saved). Compared with no screening, not-dominated strategies with ICUR and ICER less than three times China’s GDP per capita (76,824 CNY, 2009) were considered to be ‘cost-effective’ options. Among the identified ‘cost-effective’ options, the strategy with lowest ICUR or ICER was defined as the most cost-effective strategy, and the strategy with the highest health benefit (largest QALY saved or life year saved) was defined as the most effective strategy. Sensitivity analyses were conducted to test the effect of uncertainties on decision making. / Results: / All of the VIA and Pap smear screening strategies of showed certain benefits due to the decreased number of women developing cervical cancer, when compared with no screening. A trend for shorter screening interval to have greater benefit was also found. Cervical cancer mortality and incidence were expected to be reduced by 6.67-31.95% and 5.12-24.71% with different screening strategies. And the predicted relative risks of CIN and invasive cervical cancer of 0.89-0.98 and 0.73-0.95, respectively, also demonstrated the protective effect of screenings. / Modeling cost-utility analysis identified ten years VIA screening as the most cost-effective strategy followed by VIA screening with five-, three- and one year interval and Pap smear screening with a one year interval. Compared with no screening, the incremental costs per QALY saved of these strategies ranged from 11,921 to 26,069 Yuan (1,892-4,138 US dollars, 2012). In the meanwhile, modeling cost-effectiveness analysis also identified ten-years VIA screening as the most cost-effective strategy followed by VIA screening with five-year intervals and Pap smear screening with five-year intervals. Compared with no screening, the incremental costs per life year saved of these strategies ranged from 37,211 to 68,226 Yuan (5,906-18,830 US dollars, 2012). / Both ICUR and ICER of a selelected strategy were greatest influnced by factors related to variations in local economies , including treatment cost, screening cost and discounting rate of the cost. The influence of primary test performance of VIA was rather less than that of Pap smear due to the narrower ranges of the VIA sensitivities. Screening coverage, follow-up rate and treatment rate were also negatively associated with ICUR and ICER. Health outcome predictions and health economic analyses were mostly influenced by the uncertainties in HPV infection and CIN transitions in the natural history. Progression and regression probabilities between HPV infection and CIN were considered to be the key parameters of the simulation models. / Conclusions: / Baseline CUA and CEA results suggested that in comparison with traditional cytology screening strategies, organized VIA screening with long intervals (ten or five years) were more cost-effective options than for 35-59 years old women in normal incidence areas of rural China. The VIA screening interval can be shorten to one year in high incidence areas. Pap smear strategy with one year interval can be utilized as the most effective strategy with most lives saved when budget allows and the performances of program and test are ensured. / High coverage of the screening program, good management of screening positives, average or above performance of primary test, and lower screening and treatment costs are key elements for a cost-effective screening program. Cost-utility and cost-effectiveness analyses, such as the one conducted in this thesis study, can be considered important adjuncts to policy decision-making about public health objectives. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Li, Xue. / Thesis (Ph.D.)--Chinese University of Hong Kong, 2013. / Includes bibliographical references (leaves 388-401). / Abstracts also in Chinese; appendixes includes Chinese. / Abstract of thesis --- p.i / 中文摘要 --- p.v / ACKNOWLEDGEMENTS --- p.viii / TABLE OF CONTENTS --- p.1 / LIST OF TABLES --- p.8 / LIST OF FIGURES --- p.11 / ABBREVIATIONS --- p.12 / Chapter CHAPTER 1 --- INTRODUCTION --- p.14 / Chapter 1.1 --- Epidemiological patterns and disease burden of cervical cancer --- p.14 / Chapter 1.1.1 --- Cervical cancer incidence and mortality worldwide --- p.14 / Chapter 1.1.2 --- Risk factors for cervical cancer --- p.15 / Chapter 1.1.2.1 --- Human Papillomavirus (HPV) --- p.15 / Chapter 1.1.2.2 --- Parity --- p.16 / Chapter 1.1.2.3 --- Smoking --- p.16 / Chapter 1.1.2.4 --- Human Immunodeficiency Virus (HIV) --- p.17 / Chapter 1.1.2.5 --- Contraception --- p.17 / Chapter 1.1.2.6 --- Sexual behavior, nutrition and other factors --- p.18 / Chapter 1.1.3 --- Disease burden of cervical cancer in China --- p.18 / Chapter 1.1.3.1 --- Epidemiology of Cervical Cancer in China --- p.18 / Chapter 1.1.3.2 --- Cervical cancer in different geographic areas of China --- p.20 / Chapter 1.2 --- The need for cost-effectiveness analysis of cervical screening strategies in China --- p.21 / Chapter 1.2.1 --- Cervical cancer prevention in China --- p.21 / Chapter 1.2.2 --- Why do we need a modeling cost-effectiveness analysis? --- p.23 / Chapter 1.3 --- Natural history of cervical cancer --- p.25 / Chapter 1.3.1 --- Terminology --- p.25 / Chapter 1.3.2 --- Natural history of cervical cancer --- p.27 / Chapter 1.4 --- Secondary prevention strategies of cervical cancer --- p.29 / Chapter 1.4.1 --- Screening tests --- p.29 / Chapter 1.4.1.1 --- Cervical cytology --- p.29 / Chapter 1.4.1.2 --- Visual Inspection --- p.32 / Chapter 1.4.1.3 --- HPV testing --- p.36 / Chapter 1.4.2 --- Summary of different screening strategies all over the world --- p.37 / Chapter CHAPTER 2 --- LITERATURE REVIEW --- p.40 / Chapter 2.1 --- Background --- p.40 / Chapter 2.2 --- Objectives of the literature review --- p.41 / Chapter 2.3 --- Search strategies and results --- p.41 / Chapter 2.3.1 --- Search strategies --- p.41 / Chapter 2.3.2 --- Inclusion and exclusion criteria --- p.42 / Chapter 2.4 --- Literature results summary --- p.44 / Chapter 2.4.1 --- Methodology, target population and analytical perspective --- p.44 / Chapter 2.4.2 --- Screening test and program performance --- p.47 / Chapter 2.4.3 --- Cost and utility estimation --- p.49 / Chapter 2.4.4 --- Model parameter sources and validation --- p.53 / Chapter 2.4.5 --- Alternatives and identified cost-effective strategies --- p.58 / Chapter 2.5 --- Conclusions --- p.63 / Chapter CHAPTER 3 --- OBJECTIVES --- p.64 / Chapter 3.1 --- General Objectives --- p.64 / Chapter 3.2 --- Alternative cervical cancer screening strategies in this study --- p.64 / Chapter 3.3 --- Decision rules for recommended cost-effective options --- p.65 / Chapter 3.4 --- Analytical perspective and time horizon --- p.65 / Chapter 3.5 --- Objectives --- p.66 / Chapter 3.6 --- Analytical scenario in this study --- p.66 / Chapter 3.6.1 --- Patterns of cervical screening program delivery in rural China --- p.67 / Chapter 3.6.2 --- Demographic profile of the simulated hypothetical cohort --- p.67 / Chapter 3.6.3 --- Summary of model assumptions --- p.68 / Chapter 3.6.3.1 --- Assumptions related to screening performance and clinical practice --- p.68 / Chapter 3.6.3.2 --- Assumptions related to epidemiological characteristics of cervical cancer --- p.68 / Chapter 3.6.3.3 --- Assumptions related to economic evaluation --- p.69 / Chapter CHAPTER 4 --- METHODOLOGY --- p.70 / Chapter 4.1 --- Alternative strategies in this study --- p.70 / Chapter 4.2 --- Markov Model Developments and Applications --- p.72 / Chapter 4.2.1 --- General introduction of Markov Transition Model --- p.72 / Chapter 4.2.2 --- Structure of Markov models --- p.76 / Chapter 4.2.2.1 --- Natural history model of cervical cancer --- p.76 / Chapter 4.2.2.2 --- Structure of Pap smear and Visual Inspection screening models --- p.82 / Chapter 4.2.2.3 --- Structure of precancerous lesion and invasive cancer treatment models --- p.83 / Chapter 4.2.2.4 --- Interaction of the models --- p.85 / Chapter 4.2.3 --- Demographic profile of the hypothetical cohort --- p.86 / Chapter 4.2.4 --- Probabilities --- p.88 / Chapter 4.2.4.1 --- Identification and converting between rate and probability --- p.89 / Chapter 4.2.4.2 --- Initial probabilities --- p.90 / Chapter 4.2.4.3 --- Transition probabilities --- p.91 / Chapter 4.2.5 --- Screening, diagnosis and treatment characteristics --- p.101 / Chapter 4.2.5.1 --- Screening program characteristics --- p.101 / Chapter 4.2.5.2 --- Diagnosis test performance --- p.104 / Chapter 4.2.5.3 --- Precancerous lesions treatment characteristics --- p.104 / Chapter 4.2.5.4 --- Invasive cancer and treatment characteristics --- p.106 / Chapter 4.2.6 --- Model validation --- p.111 / Chapter 4.3 --- Cost data collection --- p.112 / Chapter 4.3.1 --- Perspective of study --- p.112 / Chapter 4.3.2 --- Selection of study sites --- p.113 / Chapter 4.3.3 --- Screening cost data collection --- p.113 / Chapter 4.3.4 --- Treatment cost data collection --- p.115 / Chapter 4.4 --- Cost-utility analysis and cost-effectiveness analysis --- p.117 / Chapter 4.4.1 --- General introduction of these two analyses --- p.117 / Chapter 4.4.2 --- Utility Estimates --- p.118 / Chapter 4.4.3 --- Screening utility and effectiveness evaluation --- p.120 / Chapter 4.4.4 --- Cost-effectiveness and cost-utility analysis method --- p.122 / Chapter 4.5 --- Time horizon and discounting rate --- p.125 / Chapter 4.6 --- Summary of modeling assumptions --- p.126 / Chapter 4.6.1 --- Assumptions related to screening performance and clinical practice --- p.126 / Chapter 4.6.2 --- Assumptions related to epidemiological characteristics of cervical cancer --- p.127 / Chapter 4.6.3 --- Assumptions related to economic evaluation --- p.128 / Chapter 4.7 --- Sensitivity analysis --- p.128 / Chapter 4.8 --- Ethical approval --- p.129 / Chapter CHAPTER 5 --- RESULTS --- p.130 / Chapter 5.1 --- Model validation --- p.130 / Chapter 5.2 --- Cost analysis results --- p.134 / Chapter 5.2.1 --- Screening costs results --- p.134 / Chapter 5.2.2 --- Treatment cost results --- p.136 / Chapter 5.2.3 --- The proportional costs breakdown for different screening strategies --- p.139 / Chapter 5.3 --- Utility estimation results --- p.141 / Chapter 5.4 --- Cost-utility analysis results --- p.144 / Chapter 5.4.1 --- Baseline analysis --- p.144 / Chapter 5.4.2 --- Influence of screening program performance --- p.148 / Chapter 5.4.2.1 --- Coverage of the screening program --- p.148 / Chapter 5.4.2.2 --- Follow up rate and treatment rate of positives --- p.155 / Chapter 5.4.3 --- Influence of screening test performance --- p.159 / Chapter 5.4.4 --- Influence of costs --- p.165 / Chapter 5.4.4.1 --- Influence of screening costs --- p.165 / Chapter 5.4.4.2 --- Influence of treatment costs --- p.168 / Chapter 5.4.5 --- Influence of discounting --- p.171 / Chapter 5.4.6 --- Summary of factors and their influences on the baseline CUA results --- p.174 / Chapter 5.5 --- Cost-Effectiveness analysis results --- p.180 / Chapter 5.5.1 --- Baseline analysis --- p.180 / Chapter 5.5.1.1 --- Life year saved --- p.181 / Chapter 5.5.1.2 --- Cervical cancer mortality reduction --- p.185 / Chapter 5.5.1.3 --- Cervical cancer incidence reduction --- p.187 / Chapter 5.5.1.4 --- Relative risk of CIN and cervical cancer --- p.189 / Chapter 5.5.1.5 --- Effectiveness summary of alternative screening strategies on the hypothetical 100,000 rural Chinese women --- p.191 / Chapter 5.5.2 --- Factors that influence the CEA results --- p.195 / Chapter 5.5.2.1 --- Best scenario analysis --- p.196 / Chapter 5.5.2.2 --- Worst scenario analysis --- p.201 / Chapter 5.5.2.3 --- Summary of the possible ranges of costs and effectiveness in different scenarios --- p.206 / Chapter 5.6 --- Sensitivity analysis --- p.209 / Chapter 5.6.1 --- Sensitivity analysis of Cost-Utility analysis results --- p.209 / Chapter 5.6.1.1 --- Tornado analysis --- p.209 / Chapter 5.6.1.2 --- One-way sensitivity analysis --- p.213 / Chapter 5.6.2 --- Sensitivity analysis of Cost-Effectiveness analysis results --- p.220 / Chapter 5.6.2.1 --- Tornado analysis --- p.220 / Chapter 5.6.2.2 --- One-way sensitivity --- p.224 / Chapter 5.6.3 --- Summary of sensitivity results --- p.236 / Chapter CHAPTER 6 --- SUMMARY, DISSICUSSION AND CONCLUSIONS --- p.240 / Chapter 6.1 --- Summary of Markov model development and validation --- p.240 / Chapter 6.1.1 --- Category and source summary of input parameters --- p.240 / Chapter 6.1.2 --- Model validation --- p.244 / Chapter 6.2 --- Summary of modeling results --- p.245 / Chapter 6.2.1 --- Summary of Cost-Utility Analysis --- p.245 / Chapter 6.2.1.2 --- Baseline analysis findings --- p.245 / Chapter 6.2.1.2 --- Influential factors on the cost-effective manner of alternative strategies --- p.246 / Chapter 6.2.2 --- Summary of Cost-Effectiveness Analysis --- p.250 / Chapter 6.2.2.1 --- Baseline analysis findings --- p.251 / Chapter 6.2.2.2 --- Possible ranges for cost and effectiveness of alternative strategies under different scenarios --- p.253 / Chapter 6.2.3 --- Summary of CUA and CEA findings --- p.257 / Chapter 6.2.4 --- Summary of sensitivity analysis --- p.259 / Chapter 6.2.4.1 --- Important variables on health outcome predictions --- p.259 / Chapter 6.2.4.2 --- Sensitive variables to the baseline CUA and CEA recommendations --- p.260 / Chapter 6.2.4.3 --- Overview of the sensitivity analysis --- p.263 / Chapter 6.3 --- Discussion --- p.264 / Chapter 6.3.1 --- Alternative strategies of cervical cancer screening in rural China --- p.264 / Chapter 6.3.1.1 --- Target ages --- p.265 / Chapter 6.3.1.2 --- Screening intervals --- p.266 / Chapter 6.3.1.3 --- Feasible primary screening tests --- p.267 / Chapter 6.3.1.4 --- Service delivering patterns --- p.269 / Chapter 6.3.1.5 --- Time horizon of this thesis study --- p.270 / Chapter 6.3.2 --- Transition probability estimation --- p.271 / Chapter 6.3.3 --- Screening and treatment cost estimation --- p.276 / Chapter 6.3.3.1 --- Representativeness of the selected counties --- p.276 / Chapter 6.3.3.2 --- Screening costs of VIA and Pap smear --- p.277 / Chapter 6.3.3.3 --- Treatment costs --- p.279 / Chapter 6.3.4 --- Utility estimation --- p.280 / Chapter 6.3.4.1 --- Instrument selection --- p.280 / Chapter 6.3.4.2 --- Utility estimation between studies --- p.281 / Chapter 6.3.5 --- Baseline cost-utility and cost-effectiveness analyses --- p.283 / Chapter 6.3.6 --- Sensitivity Analysis --- p.284 / Chapter 6.3.7 --- Strengths and limitations --- p.286 / Chapter 6.3.7.1 --- Limitations --- p.286 / Chapter 6.3.7.2 --- Strengths --- p.288 / Chapter 6.4 --- Policy implications --- p.289 / Chapter 6.4.1 --- How to manage a cost-effective cervical cancer screening program? --- p.289 / Chapter 6.4.2 --- How can VIA screening be adopted? --- p.290 / Chapter 6.4.3 --- How can Pap smear screening be adopted? --- p.291 / Chapter 6.4.4 --- Framework for policy decision making --- p.292 / Chapter 6.5 --- Conclusions --- p.295 / Chapter APPENDIX --- p.300 / Chapter Appendix 1-1 --- The 2001 Bethesda System* --- p.300 / Chapter Appendix 1-2 --- The FIGO Staging for cervical cancers* --- p.301 / Chapter Appendix 1-3 --- Cervical Cancer Screening Program in different countries --- p.302 / Chapter Appendix 4-1 --- WHO World Standardized Population Distribution (%) --- p.305 / Chapter Appendix 4-2 --- Summary of transition probabilities literature review --- p.306 / Chapter Appendix 4-3 --- Price Indices from 1978 to 2010 --- p.326 / Chapter Appendix 4-4 --- Screening Cost Questionnaire --- p.327 / Chapter Appendix 4-5 --- Programmatic Cost Survey Questionnaire --- p.339 / Chapter Appendix 4-6 --- Treatment Cost Survey Questionnaire --- p.342 / Chapter Appendix 4-7 --- EQ-5D Algorism (UK) --- p.344 / Chapter Appendix 4-8 --- Chinese Version of EQ5D----HQOL score questionnaire --- p.345 / Chapter Appendix 5-1 --- Calibrated variables and its final settings --- p.348 / Chapter Appendix 5-2 --- Cervical cancer new cases and deaths all over the world in 2008 --- p.349 / Chapter Appendix 5-3 --- Data distribution of CIN2-3 and cervical cancer treatment costs --- p.350 / Chapter Appendix 5-4 --- Relative risk of CIN and cervical cancer by age groups of alternative screening strategies --- p.361 / Chapter Appendix 5-5 --- Influence of discounting rate of life years on the CEA results --- p.363 / Chapter Appendix 5-6 --- Tornado analysis results based on the effect on QALYs predictions --- p.367 / Chapter Appendix 5-7 --- Tornado analysis results based on the effect on life-year predictions --- p.372 / Chapter Appendix 6-1 --- Summary of Markov Model Inputs and Sources --- p.377 / REFERENCE --- p.388

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A multi-wavelength laser diode based optical sensor was designed, developed and evaluated for monitoring and control microalgae growth in real-time. The sensor measures optical density of microalgae suspension at three wavelengths: 650 nm, 685 nm and 780 nm, which are commonly used for estimating microalgae biomass concentration and chlorophyll content. The sensor showed capability of measuring cell concentration up to 1.05 g L⁻¹ without sample dilution or preparation. The performance of the sensor was evaluated using both indoor photobioreactors and outdoor paddle wheel reactors. It was shown that the sensor was capable of monitoring the dynamics of the microalgae culture in real-time with high accuracy and durability. Specific growth rate (μ) and ratios of optical densities (OD ratios) at different wavelengths were calculated and were used as good indicators of the health of microalgae culture. A series of experiments was conducted to evaluate the sensor's capability of detecting environmental disturbances in microalgae systems, for instance, induced by dust or Vampirovibrio chlorellavorus, a bacteria found to cause crash of microalgae culture. Optical densities measured from the sensor were insensitive to the amount of dust that consisted of 59.7% of dry weight of microalgae in the system. However, the sensor was able to detect multiple events of introduction of dust timely by μ and OD ratios. The sensor was also capable of detecting subtle changes of culture in color that leads to a total crash of the culture before it can be differentiated by naked eye. The sensor was further integrated into an existing outdoor raceway to demonstrate the sensor's potential of being a core component to control microalgae production system. A real-time monitoring and control program along with a graphical user interface (GUI) was developed for a central control station aiming at improving resource use efficiency for biomass production.

No description available.