{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,21]],"date-time":"2026-08-21T14:05:45Z","timestamp":1787321145870,"version":"build-2736575974"},"reference-count":49,"publisher":"Wiley","issue":"8","license":[{"start":{"date-parts":[[2026,6,7]],"date-time":"2026-06-07T00:00:00Z","timestamp":1780790400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2026,6,7]],"date-time":"2026-06-07T00:00:00Z","timestamp":1780790400000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Intl Journal of Cancer"],"published-print":{"date-parts":[[2026,10,15]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:p>\n                    Air pollution significantly affects human health and mortality, including cancer\u2010related deaths. However, methodological approaches and spatial precision often vary across studies. Implementing geomatic tools to investigate mortality in vulnerable populations such as cancer patients may enhance understanding of environmental impacts. This study aimed to assess the relationship between short\u2010term air pollution exposure and mortality among cancer patients in France. A retrospective cohort of 44,268 consecutive cancer patients (2017\u20132020) was analyzed using a geomatic framework at fine spatial granularity. Air quality data (PM\n                    <jats:sub>2.5<\/jats:sub>\n                    , PM\n                    <jats:sub>10<\/jats:sub>\n                    , NO\n                    <jats:sub>2<\/jats:sub>\n                    , O\n                    <jats:sub>3<\/jats:sub>\n                    , temperature) were linked to each patient. Principal component analysis (PCA) identified exposure groups, and a random forest algorithm was applied to predict mortality. Overall, 9% of patients died during follow\u2010up. Four clusters of patients with distinct air quality profiles were identified. Clusters with the highest particulate matter levels (PM\n                    <jats:sub>2.5<\/jats:sub>\n                    , PM\n                    <jats:sub>10<\/jats:sub>\n                    , NO\n                    <jats:sub>2<\/jats:sub>\n                    ) showed increased mortality (12%\u201313%), whereas the cluster with the lowest pollution showed reduced mortality (8%) (chi\u2010square test,\n                    <jats:italic>p<\/jats:italic>\n                    \u2009&lt;\u20090.001). The prediction algorithm achieved a recall of 80%. The main predictors of death included higher temperature and elevated PM\n                    <jats:sub>2.5<\/jats:sub>\n                    within the previous 31\u2009days, as well as older age, male sex, and thoracic cancer. Short\u2010term exposure to degraded air quality, captured at an infra\u2010communal scale, is associated with excess mortality among cancer patients. The identification of a 31\u2010day lag window for predictive algorithm highlights opportunities for targeted prevention and timely public health interventions.\n                  <\/jats:p>","DOI":"10.1002\/ijc.70589","type":"journal-article","created":{"date-parts":[[2026,6,8]],"date-time":"2026-06-08T04:21:37Z","timestamp":1780892497000},"page":"2054-2065","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["High\u2010Throughput Geocoding to Assess Short\u2010Term Air Pollution in Correlation With Mortality in a French Cancer Patient Cohort"],"prefix":"10.1002","volume":"159","author":[{"given":"Loice","family":"Pokam","sequence":"first","affiliation":[{"name":"Thorax Institute Curie\u2010Montsouris H\u00f4pital Institut Curie  Paris France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jos\u00e9phine","family":"Bocquet","sequence":"additional","affiliation":[{"name":"Thorax Institute Curie\u2010Montsouris H\u00f4pital Institut Curie  Paris France"},{"name":"Department of Medical Informatics H\u00f4pital Europ\u00e9en Georges Pompidou, Assistance publique\u2013H\u00f4pitaux de Paris  Paris France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nadia","family":"H\u00e9garat","sequence":"additional","affiliation":[{"name":"Thorax Institute Curie\u2010Montsouris H\u00f4pital Institut Curie  Paris France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Julie","family":"Perlbarg\u2010Samson","sequence":"additional","affiliation":[{"name":"Medical Informatics Department Institut Curie  Paris France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Thomas","family":"Balezeau","sequence":"additional","affiliation":[{"name":"Data Department Institut Curie  Paris France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Maud","family":"Milder","sequence":"additional","affiliation":[{"name":"Data Department Institut Curie  Paris France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bastien","family":"Rance","sequence":"additional","affiliation":[{"name":"Department of Medical Informatics H\u00f4pital Europ\u00e9en Georges Pompidou, Assistance publique\u2013H\u00f4pitaux de Paris  Paris France"},{"name":"INSERM, Centre de Recherche des Cordeliers, UMRS 1138 Universit\u00e9 de Paris, Universit\u00e9 Sorbonne Paris Cit\u00e9  Paris France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hector","family":"Countouris","sequence":"additional","affiliation":[{"name":"Department of Medical Informatics H\u00f4pital Europ\u00e9en Georges Pompidou, Assistance publique\u2013H\u00f4pitaux de Paris  Paris France"},{"name":"INSERM, Centre de Recherche des Cordeliers, UMRS 1138 Universit\u00e9 de Paris, Universit\u00e9 Sorbonne Paris Cit\u00e9  Paris France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Julien","family":"Guerin","sequence":"additional","affiliation":[{"name":"Data Department Institut Curie  Paris France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Flavien","family":"Gilles","sequence":"additional","affiliation":[{"name":"Data Department Institut Curie  Paris France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jean","family":"Gaudart","sequence":"additional","affiliation":[{"name":"IRD, INSERM, SESSTIM, UMR1252, ISSPM, AP\u2010HM, BioSTIC, Biostatistics &amp; 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