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Purpose of the review: More than 50% of all gynaecological cancers can be classified as rare tumours (defined as an annual incidence of

CONCORD Working Group Members: Africa—Algeria: S Bouzbid (Registre du Cancer d’Annaba); M Hamdi-Chérif*, Z Zaidi (Registre du Cancer de Sétif); Gambia: R Swaminathan (National Cancer Registry); Lesotho: SH Nortje (Children’s Haematology Oncology Clinics - Lesotho); Libya: MM El Mistiri (Benghazi Cancer Registry); Mali: S Bayo, B Malle (Kankou Moussa University); Mauritius: SS Manraj, R Sewpaul-Sungkur (Mauritius National Cancer Registry); Nigeria: A Fabowale, OJ Ogunbiyi* (Ibadan Cancer Registry); South Africa: D Bradshaw, NIM Somdyala (Eastern Cape Province Cancer Registry); DC Stefan (Umtata University); Tunisia: L Jaidane, M Mokni (Registre du Cancer du Centre Tunisien). America (Central and South)—Argentina: I Kumcher, F Moreno (National Childhood Cancer Registry); MS González, EA Laura (Bahia Blanca Cancer Observatory); GH Calabrano, SB Espinola (Chubut Cancer Registry); B Carballo Quintero, R Fita (Registro Provincial de Tumores de Córdoba); DA Garcilazo, PL Giacciani (Registro Provincial Poblacional de Tumores de Entres Rios); MC Diumenjo, WD Laspada (Registro Provincial de Tumores de Mendoza); MA Green, MF Lanza (Registro de Cáncer de Santa Fe); SG Ibañez (Population Registry of Cancer of the Province Tierra del Fuego); Brazil: CA Lima, E Lobo de Oliveira (Registro de Câncer de Base Populacional de Aracaju); C Daniel, C Scandiuzzi (Cancer Registry of Distrito Federal); PCF De Souza, CD Melo (Registro de Câncer de Base Populacional de Cuiabá); K Del Pino, C Laporte (Registro de Curitiba); MP Curado, JC de Oliveira (Registro de Goiânia); CLA Veneziano, DB Veneziano (Registro de Câncer de Base Populacional de Jaú); MRDO Latorre, LF Tanaka (Registro de Câncer de São Paulo); G Azevedo e Silva* (University of Rio de Janeiro); Chile: JC Galaz, JA Moya (Registro Poblacional de Cáncer Region de Antofagasta); DA Herrmann, S Vargas (Registro Poblacional Region de Los Rios); Colombia: VM Herrera, CJ Uribe (Registro Poblacional de Cáncer Area Metropolitana de Bucaramanga); LE Bravo (Cali Cancer Registry); NE Arias-Ortiz (Registro Poblacional de Cáncer de Manizales); DM Jurado, MC Yépez Chamorro (Registro Poblacional de Cáncer del Municipio de Pasto); Cuba: YH Galán Alvarez, P Torres (Registro Nacional de Cáncer de Cuba); Ecuador: F Martínez-Reyes, ML Pérez-Meza (Cuenca Tumor Registry); L Jaramillo, R Quinto (Guayaquil Cancer Registry); P Cueva, JG Yépez (Quito Cancer Registry); Puerto Rico: CR Torres-Cintrón, G Tortolero-Luna (Puerto Rico Central Cancer Registry); Uruguay: R Alonso, E Barrios (Registro Nacional de Cáncer). America (North)—Canada: C Nikiforuk, L Shack (Alberta Cancer Registry); AJ Coldman, RR Woods (British Columbia Cancer Registry); G Noonan, D Turner* (Manitoba Cancer Registry); E Kumar, B Zhang (New Brunswick Provincial Cancer Registry); FR McCrate, S Ryan (Newfoundland & Labrador Cancer Registry); H Hannah (Northwest Territories Cancer Registry); RAD Dewar, M MacIntyre (Nova Scotia Cancer Registry); A Lalany, M Ruta (Nunavut Department of Health and Social Services); L Marrett, DE Nishri* (Ontario Cancer Registry); CA McClure, KA Vriends (Prince Edward Island Cancer Registry); C Bertrand, R Louchini (Registre Québécois du Cancer); KI Robb, H Stuart-Panko (Saskatchewan Cancer Agency); S Demers, S Wright (Yukon Government); USA: JT George, X Shen (Alabama Statewide Cancer Registry); JT Brockhouse, DK O’Brien (Alaska Cancer Registry); L Almon (Metropolitan Atlanta Registry); J Bates (California State Cancer Registry); R Rycroft (Colorado Central Cancer Registry); L Mueller, CE Phillips (Connecticut Tumor Registry); H Brown, B Cromartie (Delaware Cancer Registry); AG Schwartz, F Vigneau (Metropolitan Detroit Cancer Surveillance System); JA MacKinnon, B Wohler (Florida Cancer Data System); R Bayakly (Georgia Cancer Registry); KC Ward (Georgia Cancer Registry; Metropolitan Atlanta Registry); CA Clarke, SL Glaser (Greater Bay Area Cancer Registry); D West (Cancer Registry of Greater California); MD Green, BY Hernandez (Hawaii Tumor Registry); CJ Johnson, D Jozwik (Cancer Data Registry of Idaho); ME Charlton, CF Lynch (State Health Registry of Iowa); B Huang, TC Tucker* (Kentucky Cancer Registry); D Deapen, L Liu (Los Angeles Cancer Surveillance Program); MC Hsieh, XC Wu (Louisiana Tumor Registry); K Stern (Maryland Cancer Registry); ST Gershman, RC Knowlton (Massachusetts Cancer Registry); G Alverson, GE Copeland (Michigan State Cancer Surveillance Program); DB Rogers (Mississippi Cancer Registry); D Lemons, LL Williamson (Montana Central Tumor Registry); M Hood (Nebraska Cancer Registry); GM Hosain, JR Rees (New Hampshire State Cancer Registry); KS Pawlish, A Stroup (New Jersey State Cancer Registry); C Key, C Wiggins (New Mexico Tumor Registry); AR Kahn, MJ Schymura (New York State Cancer Registry); G Leung, C Rao (North Carolina Central Cancer Registry); LK Giljahn, B Warther (Ohio Cancer Incidence Surveillance System); A Pate (Oklahoma Central Cancer Registry); M Patil, SS Schubert (Oregon State Cancer Registry); JJ Rubertone, SJ Slack (Pennsylvania Cancer Registry); JP Fulton, DL Rousseau (Rhode Island Cancer Registry); TA Janes, SM Schwartz (Seattle Cancer Surveillance System); SW Bolick, DM Hurley (South Carolina Central Cancer Registry); J Richards, MA Whiteside (Tennessee Cancer Registry); LM Nogueira (Texas Cancer Registry); K Herget, C Sweeney (Utah Cancer Registry); J Martin, S Wang (Virginia Cancer Registry); DG Harrelson, MB Keitheri Cheteri (Washington State Cancer Registry); S Farley, AG Hudson (West Virginia Cancer Registry); R Borchers, L Stephenson (Wisconsin Department of Health Services); JR Espinoza (Wyoming Cancer Surveillance Program); HK Weir* (Centers for Disease Control and Prevention); BK Edwards* (National Cancer Institute). Asia—China: N Wang, L Yang (Beijing Cancer Registry); JS Chen (Changle City Cancer Registry); GH Song (Cixian Cancer Registry); XP Gu (Dafeng County Center for Disease Control and Prevention); P Zhang (Dalian Centers for Disease Prevention and Control); HM Ge (Donghai County Center for Disease Prevention and Control); DL Zhao (Feicheng County Cancer Registry); JH Zhang (Ganyu Center for Disease Prevention and Control); FD Zhu (Guanyun Cancer Registry); JG Tang (Haimen Cancer Registry); Y Shen (Haining City Cancer Registry); J Wang (Jianhu Cancer Registry); QL Li (Jiashan County Cancer Registry); XP Yang (Jintan Cancer Registry); J Dong, W Li (Lianyungang Center for Disease Prevention and Control); LP Cheng (Henan Province Central Cancer Registry); JG Chen (Qidong County Cancer Registry); QH Huang (Sihui Cancer Registry); SQ Huang (Taixing Cancer Registry); GP Guo (Cancer Institute of Yangzhong City); K Wei (Zhongshan City Cancer Registry); WQ Chen*, H Zeng (The National Cancer Center); Cyprus: AV Demetriou, P Pavlou (Cyprus Cancer Registry); Hong Kong: WK Mang, KC Ngan (Hong Kong Cancer Registry); India: R Swaminathan (Chennai Cancer Registry); AC Kataki, M Krishnatreya (Guwahati Cancer Registry); PA Jayalekshmi, P Sebastian (Karunagappally Cancer Registry); SD Sapkota, Y Verma (Population Based Cancer Registry, Sikkim); A Nandakumar* (National Centre for Disease Informatics and Research); Indonesia: E Suzanna (Jakarta Cancer Registry); Israel: L Keinan-Boker, BG Silverman (Israel National Cancer Registry); Japan: H Ito, H Nakagawa (Aichi Cancer Registry); M Hattori, Y Kaizaki (Fukui Cancer Registry); H Sugiyama, M Utada (Hiroshima Prefecture Cancer Registry); K Katayama, H Narimatsu (Kanagawa Cancer Registry); S Kanemura (Miyagi Prefectural Cancer Registry); T Koike (Niigata Prefecture Cancer Registry); I Miyashiro (Osaka Cancer Registry); M Yoshii (Saga Prefectural Cancer Registry); I Oki (Tochigi Prefectural Cancer Registry); A Shibata (Yamagata Prefectural Cancer Registry); T Matsuda* (National Cancer Center); Jordan: O Nimri (Jordan National Cancer Registry); Korea: KW Jung, YJ Won (Korea Central Cancer Registry); Malaysia: A Ab Manan (Malaysia National Cancer Registry); N Bhoo-Pathy (University of Malaya); Mongolia: S Tuvshingerel (Cancer Registry of Mongolia); C Ochir (Mongolian National University of Medical Sciences); Qatar: AM Al Khater, MM El Mistiri (Qatar Cancer Registry); Saudi Arabia: H Al-Eid (Saudi National Cancer Registry); Taiwan: CJ Chiang, MS Lai (Taiwan Cancer Registry); Thailand: K Suwanrungruang, S Wiangnon (Khon Kaen Provincial Cancer Registry); K Daoprasert, D Pongnikorn (Lampang Cancer Registry); SL Geater, H Sriplung (Songkhla Cancer Registry); Turkey: S Eser, CI Yakut (Izmir Cancer Registry). Europe—Austria: M Hackl (Austrian National Cancer Registry); H Mühlböck, W Oberaigner (Tyrol Cancer Registry); Belarus: AA Zborovskaya (Belarus Childhood Cancer Subregistry); OV Aleinikova (Belarusian Research Center for Pediatric Oncology, Hematology and Immunology); Belgium: K Henau, L Van Eycken (Belgian Cancer Registry); Bulgaria: N Dimitrova, Z Valerianova (Bulgarian National Cancer Registry); Croatia: M Šekerija (Croatian National Cancer Registry); Czech Republic: M Zvolský (Czech National Cancer Registry); Denmark: G Engholm, H Storm* (Danish Cancer Society); Estonia: K Innos, M Mägi (Estonian Cancer Registry); Finland: N Malila, K Seppä (Cancer Society of Finland); France: J Jégu, M Velten (Bas-Rhin General Cancer Registry); E Cornet, X Troussard (Registre Régional des Hémopathies Malignes de Basse Normandie); AM Bouvier, J Faivre (Registre Bourguignon des Cancers Digestifs); AV Guizard (Registre Général des Tumeurs du Calvados); V Bouvier, G Launoy (Registre des Tumeurs Digestives du Calvados); P Arveux (Breast cancers registry of Côte-d’Or France); M Maynadié, M Mounier (Hémopathies Malignes de Côte d’Or); E Fournier, AS Woronoff (Doubs and Belfort Territory General Cancer Registry); M Daoulas (Finistère Cancer Registry); J Clavel (French National Registry of Childhood Hematopoietic Malignancies); S Le Guyader-Peyrou (Registre des Hémopathies Malignes de la Gironde); A Monnereau (Registre des Hémopathies Malignes de la Gironde; French Network of Cancer Registries (FRANCIM)); B Trétarre (Registre des Tumeurs de l’Hérault); M Colonna (Registre du Cancer du Département de l’Isère); A Cowppli-Bony, F Molinié (Loire-Atlantique-Vendée Cancer Registry); S Bara, D Degré (Manche Cancer Registry); O Ganry, B Lapôtre-Ledoux (Registre du Cancer de la Somme); P Grosclaude (Tarn Cancer Registry); A Belot (Hospices Civils de Lyon); F Bray*, M Piñeros* (International Agency for Research on Cancer); F Sassi (Organisation for Economic Co-operation and Development); J Estève (Université Claude Bernard, Lyon); Germany: R Stabenow (Common Cancer Registry of the Federal States); A Eberle (Bremen Cancer Registry); C Erb, AL Nennecke (Hamburg Cancer Registry); J Kieschke, E Sirri (Epidemiological Cancer Registry of Lower Saxony); H Kajueter (North Rhine Westphalia Cancer Registry); K Emrich, SR Zeissig (Rhineland Palatinate Cancer Registry); B Holleczek (Saarland Cancer Registry); N Eisemann, A Katalinic (Schleswig-Holstein Cancer Registry); H Brenner (German Cancer Research Center); Gibraltar: RA Asquez, V Kumar (Gibraltar Cancer Registry); Iceland: EJ Ólafsdóttir, L Tryggvadóttir (Icelandic Cancer Registry, Icelandic Cancer Society); Ireland: H Comber, PM Walsh (National Cancer Registry Ireland); H Sundseth* (European Institute of Women’s Health); Italy: G Mazzoleni, F Vittadello (Registro Tumori Alto Adige); A Giacomin† (Piedmont Cancer Registry Provinces of Biella and Vercelli); F Bella, M Castaing (Integrated Cancer Registry of Catania-Messina-Siracusa-Enna); A Sutera Sardo (Registro Tumori Catanzaro); G Gola (Registro Tumori della Provincia di Como); S Ferretti (Registro Tumori della Provincia di Ferrara); D Serraino, A Zucchetto (Registro Tumori del Friuli Venezia Giulia); R Lillini, M Vercelli (Registro Tumori Regione Liguria); S Busco, F Pannozzo (Registro Tumori della Provincia di Latina); S Vitarelli (Registro Tumori della Provincia di Macerata); P Ricci (Registro Tumori Mantova); C Pascucci (Registro Tumori Marche Childhood); AG Russo (Registro Tumori Milano); C Cirilli, M Federico (Registro Tumori della Provincia di Modena); M Fusco, MF Vitale (Registro Tumori della ASL Napoli 3 Sud); M Usala (Nuoro Cancer Registry); R Cusimano, W Mazzucco (Registro Tumori di Palermo e Provincia); M Michiara, P Sgargi (Registro Tumori della Provincia di Parma); MM Maule, C Sacerdote (Piedmont Childhood Cancer Registry); R Tumino (Registro Tumori della Provincia di Ragusa); L Mangone (Registro Tumori Reggio Emilia); F Falcini (Registro Tumori della Romagna); L Cremone (Registro Tumori Salerno); M Budroni, R Cesaraccio (Registro Tumori della Provincia di Sassari); A Madeddu, F Tisano (Registro Tumori Siracusa); S Maspero, R Tessandori (Registro Tumori della Provincia di Sondrio); G Candela, T Scuderi (Registro Tumori Trapani); S Piffer (Registro Tumori Trento); S Rosso, L Sacchetto (Piedmont Cancer Registry); A Caldarella (Registro Tumori della Regione Toscana); F Bianconi, F Stracci (Registro Tumori Umbro di Popolazione); P Contiero, G Tagliabue (Registro Tumori Lombardia, Provincia di Varese); AP Dei Tos, M Zorzi (Registro Tumori Veneto); F Berrino*, G Gatta, M Sant* (Fondazione IRCCS Istituto Nazionale dei Tumori); R Zanetti* (International Association of Cancer Registries); R Capocaccia*, R De Angelis (National Centre for Epidemiology); Latvia: E Liepina, A Maurina (Latvian Cancer Registry); Lithuania: I Vincerževskienė (Lithuanian Cancer Registry); Malta: D Agius, N Calleja (Malta National Cancer Registry); Netherlands: S Siesling, O Visser (Netherlands Cancer Registry, IKNL); Norway: S Larønningen, B Møller (The Cancer Registry of Norway); Poland: A Dyzmann-Sroka, M Trojanowski (Greater Poland Cancer Registry); S Góźdź, R Mężyk (Holy Cross Cancer Registry); J Błaszczyk, K Kępska (Lower Silesian Cancer Registry); M Grądalska-Lampart, AU Radziszewska (Subcarpathian Cancer Registry); JA Didkowska, U Wojciechowska (National Cancer Registry); M Bielska-Lasota, K Kwiatkowska (National Institute of Public Health, NIH); Portugal: G Forjaz de Lacerda, RA Rego (Registo Oncológico Regional dos Açores); J Bastos, MA Silva (Registo Oncológico Regional do Centro); L Antunes, MJ Bento (Registo Oncológico Regional do Norte); A Mayer-da-Silva, A Miranda (Registo Oncólogico Regional do Sul); Romania: D Coza, AI Todescu (Cancer Institute I. Chiricuta); Russia: MY Valkov (Arkhangelsk Regional Cancer Registry); Slovakia: J Adamcik, C Safaei Diba (National Cancer Registry of Slovakia); Slovenia: M Primic-Žakelj, T Žagar (Cancer Registry of Republic of Slovenia); J Stare (University of Ljubljana); Spain: E Almar, A Mateos (Registro de Cáncer de Albacete); JR Quirós (Registro de Tumores del Principado de Asturias); J Bidaurrazaga, N Larrañaga (Basque Country Cancer Registry); JM Díaz García, AI Navarro (Registro de Cáncer de Cuenca); R Marcos-Gragera, ML Vilardell Gil (Epidemiology Unit and Girona Cancer Registry); E Molina, MJ Sánchez Perez (Granada Cancer Registry); P Franch Sureda, M Ramos Montserrat (Mallorca Cancer Registry); MD Chirlaque, C Navarro (Murcia Cancer Registry); E Ardanaz, CC Moreno-Iribas (Registro de Cáncer de Navarra, CIBERESP); R Fernández-Delgado, R Peris-Bonet (Registro Español de Tumores Infantiles); J Galceran (Tarragona Cancer Registry); Sweden: S Khan, M Lambe (Swedish Cancer Registry); Switzerland: B Camey (Registre Fribourgeois des Tumeurs); C Bouchardy, M Usel (Geneva Cancer Registry); H Frick, C Herrmann (Cancer Registry Grisons and Glarus; Cancer Registry of St Gallen-Appenzell); JL Bulliard, M Maspoli-Conconi (Registre Neuchâtelois et Jurassien des Tumeurs); CE Kuehni, M Schindler (Swiss Childhood Cancer Registry); A Bordoni, A Spitale (Registro Tumori Canton Ticino); A Chiolero, I Konzelmann (Registre Valaisan des Tumeurs); KL Matthes (Cancer Registry Zürich and Zug); United Kingdom: J Rashbass (National Cancer Registration and Analysis Service England); D Fitzpatrick, A Gavin (Northern Ireland Cancer Registry); RJ Black, DH Brewster (Scottish Cancer Registry); CA Stiller (National Cancer Registration and Analysis Service, Public Health England); DW Huws, C White (Welsh Cancer Intelligence & Surveillance Unit); C Allemani*, A Bonaventure, MP Coleman*, V Di Carlo, R Harewood, M Matz, M Nikšić, B Rachet* (London School of Hygiene & Tropical Medicine); R Stephens* (National Cancer Research Institute, London); F Bannon (Queens University, Belfast). Oceania—Australia: E Chalker, L Newman (Australian Capital Territory Cancer Registry); D Baker, MJ Soeberg (NSW Cancer Registry); J Aitken, C Scott (Queensland Cancer Registry); BC Stokes, A Venn (Tasmanian Cancer Registry); H Farrugia, GG Giles (Victorian Cancer Registry); T Threlfall (Western Australian Cancer Registry); D Currow*, H You (Cancer Institute NSW); New Zealand: J Hendrix, C Lewis (New Zealand Cancer Registry). Background: Primary liver cancer is the fifth most common cancer world-wide, and the second most common cause of death from cancer, with an estimated 841,100 new cases and 781,500 deaths each year. Hepatocellular carcinoma (HCC) accounts for 60–80% of cases, and cholangiocarcinoma 10–40%. We examined global trends in survival for both these sub-types of liver cancer, by country, age, sex and calendar period. Methods: Data on 1,005,032 adults (aged 15–99 years) diagnosed with a primary, invasive malignant neoplasm of the liver or intrahepatic bile ducts between 1995 and 2009 were provided by 243 population-based cancer registries in 60 countries. Analysis was restricted to patients for whom the diagnosis of a primary malignancy had been confirmed by histological or cytological examination, or assignation of a specific morphology code, and to registries from which survival estimates were considered reliable. We estimated both five-year net survival and conditional five-year net survival, for patients who survived to the first anniversary of diagnosis. Funnel plots were used to examine international variation in survival and variation by age and morphology. Results: Data on 578,740 patients from 187 registries in 36 countries were included after quality control. For patients diagnosed during 2004–2009, the pooled estimate of age-standardised five-year net survival for liver cancer was 14.8% (range, 4.4–23.7%), higher than for patients diagnosed during 1995–2000 (11.0%). Survival for patients diagnosed with HCC during 2004–2009 (pooled estimate 17.4%, range 7.7–25.5%) was higher than for those with cholangiocarcinoma (8.4%, range 3.7–16.0%). Survival for patients diagnosed during 2004–2009 was higher in Canada, Italy, Japan, Taiwan and Korea (21.2–23.7%) than the pooled estimate for patients diagnosed some 10 years earlier (1995–2000; 11.0%). Conditional survival in 2004–2009 was also higher in New Zealand, Canada, Taiwan, Korea, and China (42.0–52.7%) than the pooled estimate for 1995–2000 (33.2%). Conclusions: Survival from primary cancers of the liver has increased, but it remains poor in most countries we have examined. International variation in survival highlights the potential to improve outcomes, but prevention must also remain a priority. There is a need for continued and expanded surveillance of survival, especially in low- and middle-income countries, to assess the impact of interventions in policy and treatment. Greater consistency in registration practice and coding of liver cancer would reduce the variation in data quality and further improve the comparability of survival estimates

Patients with soft tissue sarcoma (STS) experienced better outcomes when treated according to existing clinical practice guidelines either at reference institution or dedicated treatment networks. Despite increasing evidence supporting referral to sarcoma specialised units, up to half of patients are not managed according to guidelines, particularly those in the early stage of their disease requiring surgery. Also, criteria to certify expertise of institutions, such as the treatment volume, are debated and health authorities have only recently started identification of these centres and creation of treatment networks in Europe as well as in several countries. This process have important implications for both patient outcomes and innovation of existing treatment strategies through clinical research, making improvement of clinical pathways a priority for health care authorities. This article will discuss issues with management of patients with STS, such as pathological diagnosis and adherence to guidelines, and the definition of referral centres and networks will be illustrated along with existing experiences and population-based data.

To evaluate the impact of faecal immunochemical test (FIT) screening on stage distribution at diagnosis, and to estimate relative incidence rates by stage in screened at first and subsequent rounds vs. unscreened. We included all incident cases occurring in 2000-2008 in 50- to 71-year-olds residing in areas with an FIT-screening programme. Multinomial logistic models were computed to estimate the relative risk ratio (RRR) of stages I and IV, compared to stage II + III, adjusting for age, sex, geographical area, and incidence year. Proportions were then used to estimate incidence rate ratios (IRR) by stage for screened subjects at the first and at subsequent rounds vs. unscreened subjects, applying the expected changes in overall incidence during screening phases. 11,663 cancers were included: 5965 in not-invited and 5,698 in invited subjects, 3,425 of whom attendees. Compared to not-invited, invited subjects had RRR 2.04 (95% CI: 1.84; 2.46) of stage I and RRR 0.77 (95% CI: 0.69; 0.87) of stage IV. Differences were stronger comparing attendees vs. nonattendees. Interval cancers were more frequently stage I compared to non-invited (RRR 1.54; 95% CI: 1.15; 2.04), but there was no difference for stage IV. IRRs in screened at first round vs. unscreened were 4.6 (95% CI: 4.2; 5.1), 1.4 (95% CI: 1.3; 1.5) and 0.7 (95% CI: 0.6; 0.9) for stages I, II + III and IV, respectively; in the following rounds the IRRs of screened vs. unscreened were 1.4 (95% CI: 1.2; 1.6), 0.8 (95% CI: 0.7; 0.9) and 0.3 (95% CI: 0.1; 0.4) for stages I, II + III and IV, respectively. FIT screening reduces the incidence of metastatic cancers by about 70% after the first round.

Kaposi sarcoma (KS) is a virus-related malignancy which most frequently arises in skin, though visceral sites can also be involved. Infection with Kaposi sarcoma herpes virus (KSHV or HHV-8) is required for development of KS. Nowadays, most cases worldwide occur in persons who are immunosuppressed, usually because of HIV infection or as a result of therapy to combat rejection of a transplanted organ, but classic Kaposi sarcoma is predominantly a disease of the elderly without apparent immunosuppression. We analyzed 2667 KS incident cases diagnosed during 1995-2002 and registered by 75 population-based European cancer registries contributing to the RARECARE project. Total crude and age-standardized incidence rate was 0.3 per 100,000 per year with an estimated 1642 new cases per year in the EU27 countries. Age-standardized incidence rate was 0.8 per 100,000 in Southern Europe but below 0.3 per 100,000 in all other regions. The elevated rate in southern Europe was attributable to a combination of classic Kaposi sarcoma in some Mediterranean countries and the relatively high incidence of AIDS in several countries. Five-year relative survival for 2000-2002 by the period method was 75%. More than 10,000 persons were estimated to be alive in Europe at the beginning of 2008 with a past diagnosis of KS. The aetiological link with suppressed immunity means that many people alive following diagnosis of KS suffer comorbidity from a pre-existing condition. While KS is a rare cancer, it has a relatively good prognosis and so the number of people affected by it is quite large. Thus it provides a notable example of the importance of networking in diagnosis, therapy and research for rare cancers.

BACKGROUND Cancer survival in persons with AIDS (PWA) after introduction of antiretroviral therapies remains poorly characterized. The aim is to provide population-based estimates of cancer survival, overall and for the most important cancer types in PWA, and a comparison with persons without AIDS (non-PWA) affected by the same cancer. METHODS PWA with cancer at AIDS diagnosis or thereafter were individually matched with non-PWA by type of cancer, sex, age, year of diagnosis, area of living, and, for lymphomas, histological subtype. Five-year observed survival and hazard ratios (HRs) of death in PWA versus non-PWA with 95% confidence intervals (CIs) were estimated. RESULTS We included 2262 Italian PWA and 4602 non-PWA with cancer diagnosed during 1986-2005. Between 1986 and 1995, and 1996 and 2005, 5-year survival for all cancers in PWA improved from 12% to 41% and the corresponding HR versus non-PWA decreased from 5.1 (95% CI: 4.3 to 6.1) to 2.9 (95% CI: 2.6 to 3.3). During 1996-2005, HRs were 2.0 (95% CI: 1.4 to 2.9) for Kaposi sarcoma, 3.4 (95% CI: 2.9 to 4.1) for non-Hodgkin lymphoma, and 2.4 (95% CI: 1.4 to 4.0) for cervical cancer. HRs were 2.5 (95% CI: 2.1 to 3.1) for all non-AIDS-defining cancers, 5.9 (95% CI: 3.1 to 11.2) for Hodgkin lymphoma, and 7.3 (95% CI: 2.8 to 19.2) for nonmelanoma skin cancer. A ≤3-fold survival difference was found for cancers of the stomach, liver, anus, lung, brain, and the most aggressive lymphoma subtypes. CONCLUSIONS The persisting, although narrowing, gap in cancer survival between PWA and non-PWA indicates the necessity of enhancing therapeutic approaches, so that PWA can be provided the same chances of survival observed in the general population, and improving cancer prevention and screening.

Objectives To evaluate screening patterns within organized cervical screening programs (OCSPs) and survival of women with invasive cervical cancer (ICC). Methods A population-based study was conducted in Italian areas covered by cancer registries and OCSPs. The study included all women aged 25–65 years diagnosed with ICC between 1995 and 2008, and their screening histories within OCSPs were retrieved. Hazard ratios (HR) of death and 95% confidence intervals (CI) were computed according to screening pattern, using Cox models adjusted for age, ICC stage, and major confounders. Results Among 3268 women with ICC, 20% were never-invited to OCSP, 36% were never-compliant with OCSP's invitation, 33% were compliant and had a screen-detected ICC within OCSP (i.e., after a positive cytology), and 11% were compliant but had a non-screen-detected ICC. Screen-detected ICCs were more frequently micro-invasive (42%) compared to non-screen-detected ones (14%). Compared to women with screen-detected ICC, the adjusted HRs of death were 1.9 (95% CI 1.5–2.4) for those never-invited, 2.0 (95% CI 1.6–2.5) for never-compliant, and 1.7 (95% CI 1.3–2.4) for compliant women having non-screen-detected ICC. Conclusion Prolonged survival, beyond down-staging, of women with ICC detected within OCSPs in Italy, further calls for improvements of OCSPs' invitational coverage and participation.

Reply: An inverse association between tumour size and overdiagnosis may explain the results by Bucchi et al

The incidence of vulvar squamous cell carcinoma has increased for decades in most Western countries - a trend virtually restricted to women aged50 or 60 years. In southern Europe, conversely, the trends have been insufficiently studied. This article reports a study from Italy.Thirty-eight local cancer registries, currently covering 15,274,070 women, equivalent to 49.2% of the Italian national female population, participated. Invasive cancers registered between 1990 and 2015 with an International Classification of Diseases for Oncology, 3rd revision, topography code C51 and morphology codes compatible with vulvar squamous cell carcinoma (n = 6294) were eligible. Incidence trends were analysed using joinpoint regression models, with calculation of the estimated annual percent change (EAPC), and age-period-cohort models.Total incidence showed a regular and significant decreasing trend (EAPC, -0.96; 95% confidence interval (CI), -1.43 to -0.48). This was entirely accounted for by women aged ≥60 years (EAPC, -1.34; 95% CI, -1.86 to -0.81). For younger women, the EAPC between 1990 and 2012 was 1.20 (95% CI, 0.34 to 2.06) with a non-significant acceleration thereafter. This pattern did not vary substantially in a sensitivity analysis for the effect of geographic area and duration of the registry. The age-period-cohort analysis revealed a risk decrease in cohorts born between 1905 and 1940 and a new increase in cohorts born since 1945.The decreasing trend observed among older women and the resulting decrease in total rate are at variance with reports from most Western countries. Age-period-cohort analysis confirmed a decreasing trend for earliest birth cohorts and an opposite one for recent ones.

Data are becoming the cornerstone of many businesses and entire systems infrastructure. Intelligent Transportation Systems (ITS) are no different. The ability of intelligent vehicles and devices to acquire and share environmental measurements in the form of data is leading to the creation of smart services for the benefit of individuals. In this paper, we present a system architecture to promote the development of ITS using distributed ledgers and related technologies. Thanks to these, it becomes possible to create, store and share data generated by users through the sensors on their devices or vehicles, while on the move. We propose an architecture based on Distributed Ledger Technologies (DLTs) to offer features such as immutability, traceability and verifiability of data. IOTA, a promising DLT for IoT, is used together with Decentralized File Storages (DFSes) to store and certify data (and their related metadata) coming from vehicles or by the users' devices themselves (smartphones). Ethereum is then exploited as the smart contract platform that coordinates the data sharing through access control mechanisms. Privacy guarantees are provided by the usage of distributed key management systems and Zero Knowledge Proof. We provide experimental results of a testbed based on real traces, in order to understand if DLT and DFS technologies are ready to support complex services, such as those that pertain to ITS. Results clearly show that, while the viability of the proposal cannot be rejected, further work is needed on the responsiveness of DLT infrastructures.

Highlights • Research question: how cancer impacts on LE changes during patients’ entire life • LE increased in patients surviving the first years and decreasing thereafter. • Patients’ LE in the end approached but seldom reached the general population’s LE. • This method describes when cancer survivors’ excess risk of death became negligible. • Life expectancy indicator is easy to be understood and interpreted by patients., Graphical abstract, The aims of this study were to provide life expectancy (LE) estimates of cancer patients at diagnosis and LE changes over time since diagnosis to describe the impact of cancer during patients' entire lives. Cancer patients' LE was calculated by standard period life table methodology using the relative survival of Italian patients diagnosed in population-based cancer registries in 1985–2011 with follow-up to 2013. Data were smoothed using a polynomial model and years of life lost (YLL) were calculated as the difference between patients' LE and that of the age- and sex-matched general population. The YLL at diagnosis was highest at the youngest age at diagnosis, steadily decreasing thereafter. For patients diagnosed at age 45 years, the YLL was above 20 for lung and ovarian cancers and below 6 for thyroid cancer in women and melanoma in men. LE progressively increased in patients surviving the first years, decreasing thereafter, to approach that of the general population. YLL in the long run mainly depends on attained age. Providing quantitative data is essential to better define clinical follow-up and plan health care resource allocation. These results help assess when the excess risk of death from tumour becomes negligible in cancer survivors.

Background & Aims We investigated the magnitude and temporal patterns of the decreasing trend in main performance measures of fecal immunochemical test (FIT) screening for colorectal cancer (CRC) observed in second and subsequent rounds. Methods We followed up 494,187 participants from the first round of a regional biennial FIT screening program in Italy (cut-off value for positivity, 20 μg hemoglobin/g feces) for 5 total rounds (2005–2016). At each round, only compliant participants were eligible. Performance measures from the first, third, fourth, and fifth rounds were compared with those from the second round (the first incidence round) using rate ratios from multivariate Poisson regression models and relative risk ratios from multinomial logistic regression models. Results Between the second and the third rounds, a significant 20% to 30% decrease was found in the proportion of men with a positive FIT result (from 5.2% to 4.3%) and in detection rates of advanced adenoma (from 13.4 to 10.2 per 1000), CRC (from 1.7 to 1.4 per 1000), and advanced neoplasia (from 15.1 to 11.6 per 1000). Positive predictive values (PPVs) decreased by 10% or less between the second and third rounds. Detection rates and PPVs for adenoma stabilized by the fourth and fifth rounds. The PPVs for advanced adenoma, CRC, and advanced neoplasia decreased slightly in men and women by the fourth and fifth rounds. The detection rate of proximal colon cancer stabilized after the second round, whereas the detection rate of distal colon cancer decreased until the fourth round in men (from 0.7 to 0.3 per 1000), and the fifth round in women. Conclusions These findings support the notion that FIT screening prevents progression of a subset of advanced adenomas. Screening intensity could be modulated based on results from previous rounds, with a risk-based strategy.

This paper presents an architecture of a Personal Information Management System, in which individuals can define the access to their personal data by means of smart contracts. These smart contracts, running on the Ethereum blockchain, implement access control lists and grant immutability, traceability and verifiability of the references to personal data, which is stored itself in a (possibly distributed) file system. A distributed authorization mechanism is devised, where trust from multiple network nodes is necessary to grant the access to the data. To this aim, two possible alternatives are described: a Secret Sharing scheme and Threshold Proxy Re-Encryption scheme. The performance of these alternatives is experimentally compared in terms of execution time. Threshold Proxy Re-Encryption appears to be faster in different scenarios, in particular when increasing message size, number of nodes and the threshold value, i.e. number of nodes needed to grant the data disclosure.

The aim of this paper is to understand whether Distributed Ledger Technologies (DLTs) are ready to support complex services, such as those related to Intelligent Transportation Systems (ITS). In smart transportation services, a huge amount of sensed data is generated by a multitude of vehicles. While DLTs provide very interesting features, such as immutability, traceability and verifiability of data, some doubts on the scalability and responsiveness of these technologies appear to be well-founded. We propose an architecture for ITS that resorts to DLT features. Moreover, we provide experimental results of a real test-bed over IOTA, a promising DLT for IoT. Results clearly show that, while the viability of the proposal cannot be rejected, further work is needed on the responsiveness of DLT infrastructures.

none 3 no This work presents a comprehensive and structured taxonomy of available techniques for managing the handover process in mobility architectures. Representative works from the existing literature have been divided into appropriate categories, based on their ability to support horizontal handovers, vertical handovers and multihoming. We describe approaches designed to work on the current Internet (i.e. IPv4-based networks), as well as those that have been devised for the “future” Internet (e.g. IPv6-based networks and extensions). Quantitative measures and qualitative indicators are also presented and used to evaluate and compare the examined approaches. This critical review provides some valuable guidelines and suggestions for designing and developing mobility architectures, including some practical expedients (e.g. those required in the current Internet environment), aimed to cope with the presence of NAT/firewalls and to provide support to legacy systems and several communication protocols working at the application layer. Ferretti, Stefano; Ghini, Vittorio; Panzieri, Fabio Ferretti, Stefano; Ghini, Vittorio; Panzieri, Fabio

Research on data confidentiality, integrity and availability is gaining momentum in the ICT community, due to the intrinsically insecure nature of the Internet. While many distributed systems and services are now based on secure communication protocols to avoid eavesdropping and protect confidentiality, the techniques usually employed in distributed simulations do not consider these issues at all. This is probably due to the fact that many real-world simulators rely on monolithic, offline approaches and therefore the issues above do not apply. However, the complexity of the systems to be simulated, and the rise of distributed and cloud based simulation, now impose the adoption of secure simulation architectures. This paper presents a solution to ensure both anonymity and confidentiality in distributed simulations. A performance evaluation based on an anonymized distributed simulator is used for quantifying the performance penalty for being anonymous. The obtained results show that this is a viable solution., Proceedings of the IEEE/ACM International Symposium on Distributed Simulation and Real Time Applications (DS-RT 2018)

Online gaming scalability refers to all those techniques that aim at supporting online game sessions with a variable amount of participants. No matter the amount of players, the online game session must provide a fluid, compelling, and responsive game evolution.

Client/server gaming architecture refers to a typical distributed architecture for the support of networked games. In this architecture, a single node plays the role of the server, i.e., it maintains the game state and communicates with all other nodes (the clients). The server notifies game moves generated by players and computes the game state updates.

This paper deals with the problem of properly simulating the Internet of Things (IoT). Simulating an IoT allows evaluating strategies that can be employed to deploy smart services over different kinds of territories. However, the heterogeneity of scenarios seriously complicates this task. This imposes the use of sophisticated modeling and simulation techniques. We discuss novel approaches for the provision of scalable simulation scenarios, that enable the real-time execution of massively populated IoT environments. Attention is given to novel hybrid and multi-level simulation techniques that, when combined with agent-based, adaptive Parallel and Distributed Simulation (PADS) approaches, can provide means to perform highly detailed simulations on demand. To support this claim, we detail a use case concerned with the simulation of vehicular transportation systems., Proceedings of the IEEE 2017 International Conference on High Performance Computing and Simulation (HPCS 2017)

Notes in a musical piece are building blocks employed in non-random ways to create melodies. It is the "interaction" among a limited amount of notes that allows constructing the variety of musical compositions that have been written in centuries and within different cultures. Networks are a modeling tool that is commonly employed to represent a set of entities interacting in some way. Thus, notes composing a melody can be seen as nodes of a network that are connected whenever these are played in sequence. The outcome of such a process results in a directed graph. By using complex network theory, some main metrics of musical graphs can be measured, which characterize the related musical pieces. In this paper, we define a framework to represent melodies as networks. Then, we provide an analysis on a set of guitar solos performed by main musicians. Results of this study indicate that the presented model can have an impact on audio and multimedia applications such as music classification, identification, e-learning, automatic music generation, multimedia entertainment., Comment: to appear in Information Science, Elsevier. Please cite the paper including such information. arXiv admin note: text overlap with arXiv:1603.04979

Mobility in urban environments is an undisputed key factor that can affect citizens’ well-being and quality of life. This is particularly relevant for those people with disabilities or with reduced mobility who have to face the presence of barriers in urban areas. In this scenario, the availability of information about such architectural elements (together with facilities) can greatly support citizens’ mobility by enhancing their independence and their abilities in conducting daily outdoor activities. With this in mind, we have designed and developed mobile Pervasive Accessibility Social Sensing (mPASS), a system that provides users with personalized paths, computed on the basis of their own preferences and needs, with a customizable and accessible interface. The system collects data from crowdsourcing and crowdsensing to map urban and architectural accessibility by providing reliable information coming from different data sources with different levels of trustworthiness. In this context, reliability can be ensured by properly managing crowdsourced and crowdsensed data, combined when possible with authoritative datasets, provided by disability rights organizations and local authorities. To demonstrate this claim, in this article we present our trustworthiness model and discuss results we have obtained by simulations.

In this paper, a methodology is presented and employed for simulating the Internet of Things (IoT). The requirement for scalability, due to the possibly huge amount of involved sensors and devices, and the heterogeneous scenarios that might occur, impose resorting to sophisticated modeling and simulation techniques. In particular, multi-level simulation is regarded as a main framework that allows simulating large-scale IoT environments while keeping high levels of detail, when it is needed. We consider a use case based on the deployment of smart services in decentralized territories. A two level simulator is employed, which is based on a coarse agent-based, adaptive parallel and distributed simulation approach to model the general life of simulated entities. However, when needed a finer grained simulator (based on OMNeT++) is triggered on a restricted portion of the simulated area, which allows considering all issues concerned with wireless communications. Based on this use case, it is confirmed that the ad-hoc wireless networking technologies do represent a principle tool to deploy smart services over decentralized countrysides. Moreover, the performance evaluation confirms the viability of utilizing multi-level simulation for simulating large scale IoT environments., Simulation Modelling Practice and Theory, Elsevier, vol. 73 (April 2017)

Discrete Event Simulation is a widely used technique that is used to model and analyze complex systems in many fields of science and engineering. The increasingly large size of simulation models poses a serious computational challenge, since the time needed to run a simulation can be prohibitively large. For this reason, Parallel and Distributes Simulation techniques have been proposed to take advantage of multiple execution units which are found in multicore processors, cluster of workstations or HPC systems. The current generation of HPC systems includes hundreds of thousands of computing nodes and a vast amount of ancillary components. Despite improvements in manufacturing processes, failures of some components are frequent, and the situation will get worse as larger systems are built. In this paper we describe FT-GAIA, a software-based fault-tolerant extension of the GAIA/ART\`IS parallel simulation middleware. FT-GAIA transparently replicates simulation entities and distributes them on multiple execution nodes. This allows the simulation to tolerate crash-failures of computing nodes; furthermore, FT-GAIA offers some protection against byzantine failures since synchronization messages are replicated as well, so that the receiving entity can identify and discard corrupted messages. We provide an experimental evaluation of FT-GAIA on a running prototype. Results show that a high degree of fault tolerance can be achieved, at the cost of a moderate increase in the computational load of the execution units., Comment: Proceedings of the IEEE/ACM International Symposium on Distributed Simulation and Real Time Applications (DS-RT 2016)

This paper discusses the need to devise novel strategies to create smart services specifically designed to non-metropolitan areas, i.e. countrysides. These solutions must be viable, cheap an should take into consideration the different nature of countrysides, that cannot afford the deployment of services designed for smart cities. These solutions would have an important social impact for people leaving in these countrysides, and might slow down the constant migration of citizens towards metropolis. In this work, we focus on communication technologies and practical technological/software distributed architectures. An important aspect for the real deployment of these "smart shires" is their simulation. We show that "priority-based broadcast" schemes over ad-hoc networks can represent an effective communication substrate to be used in a software middleware promoting the creation of applications for smart shire scenarios.

This paper discusses on the need to focus on effective and cheap communication solutions for the deployment of smart services in countrysides. We present the main wireless technologies, software architectures and protocols that need to be exploited, such as multihop, multipath communication and mobility support through multihoming. We present Always Best Packet Switching (ABPS), an operation mode to perform network handover in a seamless way without the need to change the current network infrastructure and configuration. This is in accordance with the need of having cheap solutions that may work in a smart shire scenario. A simulation assessment confirms the effectiveness of our approach., Proceedings of the IEEE Symposium on Computers and Communication (ISCC 2016), Messina (Italy), 2016

We model users' preference and special needs in terms of Web content legibility and readability.Our system exploits a reinforcement learning mechanism, with the aim of understanding and predicting users' behaviors and needs.Our system performs automatic adaptation of Web Content.We conducted simulations and tests with real users to confirm viability of our proposal. This paper deals with the automatic adaptation of Web contents. It is recognized that quite often users need some personalized adaptations to access Web contents. This is more evident when we focus on people with some accessibility needs. Based on the user profile, it is possible to transcode or modify contents (e.g., adapt text fonts) so as to meet the user preferences. The problem is that applying such a kind of transformations to the whole content might significantly alter Web pages that might become unreadable, hence making matters worse. We present a system that employs Web intelligence to perform automatic adaptations on single elements composing a Web page. A reinforcement learning algorithm is utilized to manage user profiles. We evaluate our system through simulation and a real assessment where elderly users where asked to use for a time period our system prototype. Results confirm the feasibility of the proposal.

This paper presents main concepts and issues concerned with the simulation of Internet of Things (IoT). The heterogeneity of possible scenarios, arising from the massive deployment of an enormous amount of sensors and devices, imposes the use of sophisticated modeling and simulation techniques. In fact, the simulation of IoT introduces several issues from both quantitative and qualitative aspects. We discuss novel simulation techniques to enhance scalability and to permit the real-time execution of massively populated IoT environments (e.g., large-scale smart cities). In particular, we claim that agent-based, adaptive Parallel and Distributed Simulation (PADS) approaches are needed, together with multi-level simulation, which provide means to perform highly detailed simulations, on demand. We present a use case concerned with the simulation of smart territories., Proceedings of the IEEE 2016 International Conference on High Performance Computing and Simulation (HPCS 2016)

This paper focuses on the trustworthiness of data gathered from different sources, including crowdsensing and crowdsourcing, in pervasive systems. The specific focus is on mPASS (mobile Pervasive Accessibility Social Sensing), a system devoted to support mobile users with accessibility needs in a smart city context. mPASS is in charge of collecting data about urban and architectural barriers and facilities, with the aim of providing mobile users with personalized paths, during their movement, computed on the basis of their preferences and accessibility needs. A trustworthiness model is presented that combines three sources of information, i.e., crowdsensed data, crowdsourced data and authoritative data. Simulations results witness the feasibility of our approach.

none 4 no This work presents mPASS (mobile Pervasive Accessibility Social Sensing), a system that exploits data crowdsourcing and crowdsensing to support urban accessibility. The system aims providing users with personalized paths, computed on the basis of user profiles and of the accessibility facilities/barriers present in the location. To perform this task, mPASS needs a set of georeferenced data dense enough and trustworthy enough to avoid false positives and negatives. With these needs in view, mPASS combines data gathered by users and sensors, with information produced by disability organizations and local authorities. In this paper, we propose a method to evaluate trustworthiness of data provided by the system, taking into account characteristics of the different data sources. We conducted a set of simulations on credibility of sources, obtaining positive results. mixed Prandi, Catia; Ferretti, Stefano; Mirri, Silvia; Salomoni, Paola Prandi, Catia; Ferretti, Stefano; Mirri, Silvia; Salomoni, Paola

none 2 no Available online 4 September 2016 This paper presents a study on data dissemination in unstructured Peer-to-Peer (P2P) network overlays. The absence of a structure in unstructured overlays eases the network management, at the cost of non-optimal mechanisms to spread messages in the network. Thus, dissemination schemes must be employed that allow covering a large portion of the network with a high probability (e.g. gossip based approaches). We identify principal metrics, provide a theoretical model and perform the assessment evaluation using a high performance simulator that is based on a parallel and distributed architecture. A main point of this study is that our simulation model considers implementation technical details, such as the use of caching and Time To Live (TTL) in message dissemination, that are usually neglected in simulations, due to the additional overhead they cause. Outcomes confirm that these technical details have an important influence on the performance of dissemination schemes and that the studied schemes are quite effective to spread information in P2P overlay networks, whatever their topology. Moreover, the practical usage of such dissemination mechanisms requires a fine tuning of many parameters, the choice between different network topologies and the assessment of behaviors such as free riding. All this can be done only using efficient simulation tools to support both the network design phase and, in some cases, at runtime. D'Angelo, Gabriele; Ferretti, Stefano D'Angelo, Gabriele; Ferretti, Stefano

Cloud computing is a service model where the provider offers computation and storage resources to customers on a “pay-as-you-go” basis (Mell and Grance 2011). The essential features of a cloud computing environment are: On-demand self-service: the ability to provide computing capabilities (e.g., CPU time, network storage) dynamically, as needed, without human intervention. Broad network access: resources can be accessed through the network by client platforms using standard mechanisms and protocols. Resource pooling: virtual and physical resources can be pooled and assigned dynamically to consumers, according to their demand, using a multitenant model. Elasticity: from the customers’ point of view, the provider offers unlimited resources that can be purchased in any quantity at any time. Measured service: cloud resource and service usages are optimized through a pay-per-use business model and are monitored, controlled, and reported transparently to both their customer and provider.