OBJECTIVE: This study aims to compare survival from breast, colon, lung, ovarian and rectal cancer by geographical remoteness in New South Wales (NSW). DESIGN: Retrospective population-wide registry study. SETTING: NSW, Australia. PARTICIPANTS: A total of 107 060 NSW residents, who were diagnosed with any of the five cancers between 01 January 2000 and 31 December 2008. MAIN OUTCOME MEASURES: Kaplan-Meier survival curves and proportional hazards regression were used to compare survival by geographical remoteness of residence at diagnosis, controlling for gender, age and extent of disease at diagnosis. Remoteness was classified using standard definitions: major city, inner regional (InnReg), outer regional (OutReg) and remote (including very remote). RESULTS: Significant differences in survival (likelihood of death) were identified in all five cancers: breast (adjusted hazard ratio(HR) = 1.22 (95% confidence interval (CI), 1.001-1.48) in regionalised and HR = 1.30 (1.02-1.64) in metastatic disease for OutReg areas); colon (HR = 1.14 (1.01-1.29) for OutReg areas in metastatic disease); lung (HR range = 1.08-1.35 (1.01-1.48) for most non-metropolitan areas in all stages of disease excepting regionalised); ovarian (HR = 1.32 (1.06-1.65) for OutReg areas in metastatic disease, HR = 1.40 (1.04-1.90) for InnReg areas and HR = 1.68 (1.02-2.77) for OutReg areas in unknown stage of disease) and rectal (HR = 1.37 (1.05-1.78) for OutReg areas in localised and HR = 1.14 (1.002-1.30) for InnReg areas in regionalised disease). Where significant differences were found, major cities tended to show the best survival, whereas OutReg areas tended to show the worst. Although no definitive interpretation could be made regarding remote areas due to small patient numbers, their survival appeared relatively favourable. CONCLUSIONS: Reasons that contribute to the differences observed and the disparate results between cancer types need to be further explored in order to facilitate targeted solutions in reducing survival inequality between NSW regions.
OBJECTIVE: This study aims to compare survival from breast, colon, lung, ovarian and rectal cancer by geographical remoteness in New South Wales (NSW). DESIGN: Retrospective population-wide registry study. SETTING: NSW, Australia. PARTICIPANTS: A total of 107 060 NSW residents, who were diagnosed with any of the five cancers between 01 January 2000 and 31 December 2008. MAIN OUTCOME MEASURES: Kaplan-Meier survival curves and proportional hazards regression were used to compare survival by geographical remoteness of residence at diagnosis, controlling for gender, age and extent of disease at diagnosis. Remoteness was classified using standard definitions: major city, inner regional (InnReg), outer regional (OutReg) and remote (including very remote). RESULTS: Significant differences in survival (likelihood of death) were identified in all five cancers: breast (adjusted hazard ratio(HR) = 1.22 (95% confidence interval (CI), 1.001-1.48) in regionalised and HR = 1.30 (1.02-1.64) in metastatic disease for OutReg areas); colon (HR = 1.14 (1.01-1.29) for OutReg areas in metastatic disease); lung (HR range = 1.08-1.35 (1.01-1.48) for most non-metropolitan areas in all stages of disease excepting regionalised); ovarian (HR = 1.32 (1.06-1.65) for OutReg areas in metastatic disease, HR = 1.40 (1.04-1.90) for InnReg areas and HR = 1.68 (1.02-2.77) for OutReg areas in unknown stage of disease) and rectal (HR = 1.37 (1.05-1.78) for OutReg areas in localised and HR = 1.14 (1.002-1.30) for InnReg areas in regionalised disease). Where significant differences were found, major cities tended to show the best survival, whereas OutReg areas tended to show the worst. Although no definitive interpretation could be made regarding remote areas due to small patient numbers, their survival appeared relatively favourable. CONCLUSIONS: Reasons that contribute to the differences observed and the disparate results between cancer types need to be further explored in order to facilitate targeted solutions in reducing survival inequality between NSW regions.
Authors: Kristin S Weeks; Charles F Lynch; Michele West; Megan McDonald; Ryan Carnahan; Sherri L Stewart; Mary Charlton Journal: J Rural Health Date: 2020-02-20 Impact factor: 5.667
Authors: Michael J Ireland; Sonja March; Fiona Crawford-Williams; Mandy Cassimatis; Joanne F Aitken; Melissa K Hyde; Suzanne K Chambers; Jiandong Sun; Jeff Dunn Journal: BMC Cancer Date: 2017-02-02 Impact factor: 4.430
Authors: Paramita Dasgupta; Peter D Baade; Danny R Youlden; Gail Garvey; Joanne F Aitken; Isabella Wallington; Jennifer Chynoweth; Helen Zorbas; Philippa H Youl Journal: BMJ Open Date: 2018-04-29 Impact factor: 2.692
Authors: Stuart Purdie; Nicola Creighton; Kahren Maree White; Deborah Baker; Dan Ewald; Chee Khoon Lee; Alison Lyon; Johnathan Man; David Michail; Alexis Andrew Miller; Lawrence Tan; David Currow; Jane M Young Journal: NPJ Prim Care Respir Med Date: 2019-02-08 Impact factor: 2.871
Authors: Shantelle Smith; Margaret Brand; Susan Harden; Lisa Briggs; Lillian Leigh; Fraser Brims; Mark Brooke; Vanessa N Brunelli; Collin Chia; Paul Dawkins; Ross Lawrenson; Mary Duffy; Sue Evans; Tracy Leong; Henry Marshall; Dainik Patel; Nick Pavlakis; Jennifer Philip; Nicole Rankin; Nimit Singhal; Emily Stone; Rebecca Tay; Shalini Vinod; Morgan Windsor; Gavin M Wright; David Leong; John Zalcberg; Rob G Stirling Journal: BMJ Open Date: 2022-08-29 Impact factor: 3.006