Morrell Stephen, Roder David, Currow David, Engel Alexander, Hovey Elizabeth, Lewis Craig R, Liauw Winston, Martin Jarad M, Patel Manish, Thompson Stephen R, O'Brien Tracey
Division of Cancer Services and Information, Cancer Institute NSW, St Leonards, NSW, Australia.
Cancer Epidemiology and Population Health, University of South Australia, Adelaide, SA, Australia.
Front Oncol. 2024 Aug 21;14:1338754. doi: 10.3389/fonc.2024.1338754. eCollection 2024.
Population cancer registries record primary cancer incidence, mortality and survival for whole populations, but not more timely outcomes such as cancer recurrence, secondary cancers or other complications that disrupt event-free survival. Nonetheless, indirect evidence may be inferred from treatment data to provide indicators of recurrence and like events, which can facilitate earlier assessment of care outcomes. The present study aims to infer such evidence by applying algorithms to linked cancer registry and treatment data obtained from hospitals and universal health insurance claims applicable to the New South Wales (NSW) population of Australia.
Primary invasive cancers from the NSW Cancer Registry (NSWCR), diagnosed in 2001-2018 with localized or regionalized summary stage, were linked to treatment data for five common Australian cancers: breast, colon/rectum, lung, prostate, and skin (melanomas). Clinicians specializing in each cancer type provided guidance on expected treatment pathways and departures to indicate remission and subsequent recurrence or other disruptive events. A sample survey of patients and clinicians served to test initial population-wide results. Following consequent refinement of the algorithms, estimates of recurrence and like events were generated. Their plausibility was assessed by their correspondence with expected outcomes by tumor type and summary stage at diagnosis and by their associations with cancer survival.
Kaplan-Meier product limit estimates indicated that 5-year cumulative probabilities of recurrence and other disruptive events were lower, and median times to these events longer, for those staged as localized rather than regionalized. For localized and regionalized cancers respectively, these were: breast - 7% (866 days) and 34% (570 days); colon/rectum - 15% (732 days) and 25% (641 days); lung - 46% (552 days) and 66% (404 days); melanoma - 11% (893 days) and 38% (611 days); and prostate - 14% (742 days) and 39% (478 days). Cases with markers for these events had poorer longer-term survival.
These population-wide estimates of recurrence and like events are approximations only. Absent more direct measures, they nonetheless may inform service planning by indicating population or treatment sub-groups at increased risk of recurrence and like events sooner than waiting for deaths to occur.
人群癌症登记处记录整个人群的原发性癌症发病率、死亡率和生存率，但不记录癌症复发、继发性癌症或其他破坏无事件生存的并发症等更及时的结果。尽管如此，可以从治疗数据中推断出间接证据，以提供复发和类似事件的指标，这有助于更早地评估护理结果。本研究旨在通过将算法应用于从医院获取的关联癌症登记和治疗数据以及适用于澳大利亚新南威尔士州（NSW）人群的全民健康保险理赔数据来推断此类证据。
将2001 - 2018年诊断为局部或区域汇总分期的新南威尔士州癌症登记处（NSWCR）的原发性侵袭性癌症与澳大利亚五种常见癌症的治疗数据相关联：乳腺癌、结肠/直肠癌、肺癌、前列腺癌和皮肤癌（黑色素瘤）。专门研究每种癌症类型的临床医生就预期治疗途径和偏离情况提供指导，以表明缓解以及随后的复发或其他破坏事件。对患者和临床医生进行抽样调查以检验最初的全人群结果。在对算法进行后续完善后，生成了复发和类似事件的估计值。通过它们与诊断时肿瘤类型和汇总分期的预期结果的对应关系以及与癌症生存的关联来评估其合理性。
Kaplan - Meier乘积限估计表明，对于分期为局部而非区域的患者，复发和其他破坏事件的5年累积概率较低，这些事件的中位时间较长。对于局部和区域癌症，分别为：乳腺癌 - 7%（866天）和34%（570天）；结肠/直肠癌 - 15%（732天）和25%（641天）；肺癌 - 46%（552天）和66%（404天）；黑色素瘤 - 11%（893天）和38%（611天）；前列腺癌 - 14%（742天）和39%（478天）。有这些事件标志物的病例长期生存率较差。
这些全人群复发和类似事件的估计值仅是近似值。在缺乏更直接测量方法的情况下，它们仍然可以通过比等待死亡发生更早地指出复发和类似事件风险增加的人群或治疗亚组，为服务规划提供参考。
