{"id":{"repo_id":"ucl","oai_identifier":"oai:eprints.ucl.ac.uk.OAI2:14896"},"canonical_url":"https://search.dev.ndltd.org/etd/ucl/oai:eprints.ucl.ac.uk.OAI2:14896","repository":{"repo_id":"ucl","name":"University College London","base_url":"https://discovery.ucl.ac.uk/cgi/oai2"},"display":{"title":"The population incidence of cancer","abstract":"In this thesis stochastic techniques are used in attempts to understand cancer risk, its relationship to patient age and genotype, as well as its distribution in human populations. The starting point for the thesis is the general observation that cancer incidence grows in approximate proportion to an integer power of age. Quasi-mechanistic mathematical models of cancer incidence have suggested that the integer power in a given case is related to the number of crucial cellular events that must occur for a malignant tumour to evolve from a healthy tissue. This idea and its limitations are explored. Further applications of cancer incidence models are then evaluated and developed. Specifically, a critical examination is presented of the notion that increases in risk associated with a particular predisposing germline gene mutation, can provide information about the disease-associated activity of that gene. Finally, there is a discussion of heterogeneity in liability to cancer. Methods for quantifying this heterogeneity and its effect on incidence patterns are investigated.","abstract_html":"In this thesis stochastic techniques are used in attempts to understand cancer risk, its relationship to patient age and genotype, as well as its distribution in human populations. The starting point for the thesis is the general observation that cancer incidence grows in approximate proportion to an integer power of age. Quasi-mechanistic mathematical models of cancer incidence have suggested that the integer power in a given case is related to the number of crucial cellular events that must occur for a malignant tumour to evolve from a healthy tissue. This idea and its limitations are explored. Further applications of cancer incidence models are then evaluated and developed. Specifically, a critical examination is presented of the notion that increases in risk associated with a particular predisposing germline gene mutation, can provide information about the disease-associated activity of that gene. Finally, there is a discussion of heterogeneity in liability to cancer. Methods for quantifying this heterogeneity and its effect on incidence patterns are investigated.","abstract_has_math":false,"creators":["Hornsby, C."],"institution":"UCL (University College London)","degree_name":null,"degree_level":"Doctoral","degree_discipline":null,"degree_department":null,"school":null,"contributors":[],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2009,"date_issued":"2009-02","date_published":"2009-02","updated_at":"2026-07-24T05:10:21Z","subjects":["Centre for Mathematics and Physical Sciences in the Life Sciences and Experimental Biology (COMPLEX)"],"languages":["en","eng"],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":null,"outbound_label":null,"outbound_source":null},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:creator","label":"Author","values":["Hornsby, C."]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2009-02"]},{"key":"dc:date.issued","label":"Date","values":["2009-02"]},{"key":"dc:publisher.department","label":"Dc Publisher Department","values":["Department of Computer Science"]},{"key":"dc:publisher.institution","label":"Dc Publisher Institution","values":["UCL (University College London)"]},{"key":"dc:relation.isreferencedby","label":"Dc Relation Isreferencedby","values":["https://discovery.ucl.ac.uk/id/eprint/14896/"]},{"key":"dc:type","label":"Dc Type","values":["Thesis"]},{"key":"dc:type.qualificationlevel","label":"Dc Type Qualificationlevel","values":["Doctoral"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Centre for Mathematics and Physical Sciences in the Life Sciences and Experimental Biology (COMPLEX)"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en","eng"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["https://discovery.ucl.ac.uk/id/eprint/14896/1/14896.pdf"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["In this thesis stochastic techniques are used in attempts to understand cancer risk, its relationship to patient age and genotype, as well as its distribution in human populations. The starting point for the thesis is the general observation that cancer incidence grows in approximate proportion to an integer power of age. Quasi-mechanistic mathematical models of cancer incidence have suggested that the integer power in a given case is related to the number of crucial cellular events that must occur for a malignant tumour to evolve from a healthy tissue. This idea and its limitations are explored. Further applications of cancer incidence models are then evaluated and developed. Specifically, a critical examination is presented of the notion that increases in risk associated with a particular predisposing germline gene mutation, can provide information about the disease-associated activity of that gene. Finally, there is a discussion of heterogeneity in liability to cancer. Methods for quantifying this heterogeneity and its effect on incidence patterns are investigated."]},{"key":"dc:format","label":"Dc Format","values":["application/pdf"]},{"key":"dc:title","label":"Title","values":["The population incidence of cancer"]}]}],"canonical_facts":{"dc:creator":["Hornsby, C."],"dc:date":["2009-02"],"dc:date.issued":["2009-02"],"dc:description.abstract":["In this thesis stochastic techniques are used in attempts to understand cancer risk, its relationship to patient age and genotype, as well as its distribution in human populations. The starting point for the thesis is the general observation that cancer incidence grows in approximate proportion to an integer power of age. Quasi-mechanistic mathematical models of cancer incidence have suggested that the integer power in a given case is related to the number of crucial cellular events that must occur for a malignant tumour to evolve from a healthy tissue. This idea and its limitations are explored. Further applications of cancer incidence models are then evaluated and developed. Specifically, a critical examination is presented of the notion that increases in risk associated with a particular predisposing germline gene mutation, can provide information about the disease-associated activity of that gene. Finally, there is a discussion of heterogeneity in liability to cancer. Methods for quantifying this heterogeneity and its effect on incidence patterns are investigated."],"dc:format":["application/pdf"],"dc:identifier.uri":["https://discovery.ucl.ac.uk/id/eprint/14896/1/14896.pdf"],"dc:language":["en","eng"],"dc:publisher.department":["Department of Computer Science"],"dc:publisher.institution":["UCL (University College London)"],"dc:relation.isreferencedby":["https://discovery.ucl.ac.uk/id/eprint/14896/"],"dc:subject":["Centre for Mathematics and Physical Sciences in the Life Sciences and Experimental Biology (COMPLEX)"],"dc:title":["The population incidence of cancer"],"dc:type":["Thesis"],"dc:type.qualificationlevel":["Doctoral"]},"updated_at":"2026-07-24T05:10:21Z"}