Hatteville Laurence, Mahe Cédric, Hill Catherine
Institut Gustave Roussy, Service de Biostatistique et d'Epidémiologie, 39 rue Camille Desmoulins, 94805 Villejuif Cedex, France.
Stat Med. 2002 Aug 30;21(16):2345-54. doi: 10.1002/sim.1046.
After a breast cancer diagnosis, single or multiple events can occur during follow-up (recurrence, metastasis, and death). An analysis of long-term survival should take into account not only the initial characteristics of the patient, but also her oncological status (that is, her history) after surgery. For this purpose, we used a technique proposed by Klein, Keiding and Copelan (1994), to predict the probability of a patient being alive 20 years after surgery for a breast cancer, based on data concerning her oncological status at time t. The first step of the model was to estimate the hazard function for each event of interest (recurrence, metastasis, and death) in a Cox model including initial patient characteristics (age, tumour size, number of involved axillary lymph nodes and the Scarff, Bloom and Richardson (SBR) histo-prognostic grade) and time-dependent covariates representing the occurrence of intermediate events (recurrence and metastasis). The second step was to use these estimations to calculate the conditional probability of being alive 20-t years later for a patient, given her oncological status at time t (t<10 years). In this second step, the method presented by Klein, Keiding and Copelan was extended to include non-proportional hazards. This model has been applied to a population of 3180 patients operated on for a breast cancer at the Institut Gustave Roussy between 1 January 1954 and 31 December 1983. At the time of surgery, the probability of survival at 20 years is 0.78 for all patients. Ten years after surgery, if no recurrence or metastasis are observed, the probability of survival at 20 years will rise to 0.89. If only a recurrence is observed, the probability of a patient being alive at 20 years will drop to 0.72. If a metastasis and no recurrence is observed, the probability of survival at 20 years will be only 0.18. If both recurrence and metastasis are observed the probability of survival at 20 years will be equal to 0.09. In conclusion, the model used dynamically appraises the prognosis and represents a new approach for studying the outcome of breast cancer patients having undergone surgery.
乳腺癌确诊后,随访期间可能会出现单次或多次事件(复发、转移和死亡)。对长期生存情况的分析不仅应考虑患者的初始特征,还应考虑其术后的肿瘤学状态(即病史)。为此,我们采用了Klein、Keiding和Copelan(1994年)提出的一种技术,根据患者在时间t时的肿瘤学状态数据,预测乳腺癌患者术后20年存活的概率。该模型的第一步是在Cox模型中估计每个感兴趣事件(复发、转移和死亡)的风险函数,该模型包括患者的初始特征(年龄、肿瘤大小、腋窝淋巴结受累数量以及斯卡夫、布鲁姆和理查森(SBR)组织预后分级)和代表中间事件(复发和转移)发生情况的时间依赖性协变量。第二步是利用这些估计值,根据患者在时间t(t<10年)时的肿瘤学状态,计算患者在20 - t年后存活的条件概率。在第二步中,Klein、Keiding和Copelan提出的方法被扩展到包括非比例风险。该模型已应用于1954年1月1日至1983年12月31日期间在古斯塔夫·鲁西研究所接受乳腺癌手术的3180名患者群体。手术时,所有患者术后20年的生存概率为0.78。术后10年,如果未观察到复发或转移,术后20年的生存概率将升至0.89。如果仅观察到复发,患者术后20年存活的概率将降至0.72。如果观察到转移但未复发,术后20年的生存概率仅为0.18。如果同时观察到复发和转移,术后20年的生存概率将等于0.09。总之,所使用的模型动态评估预后,代表了一种研究接受手术的乳腺癌患者预后的新方法。