新的臨床指標可以協助預測末期腎臟疾病患者的預後

作者：Laurie Barclay, MD  
出處：WebMD醫學新聞

　　April 7, 2010 — 根據一項線上發表於3月29日加拿大醫學會期刊的研究結果，新的臨床指標可以協助評估罹患末期腎臟疾病（ESRD）患者死亡風險。
　　
　　來自加拿大安大略渥太華大學的Carl van Walraven醫師與其同事們寫到，我們想要研發且確效一個可以正確地量化接受許多治療選擇的ESRD患者存活。我們根據目前可得資料研發這個預後指標，所以這個指標，當需要進行移植相關諮詢時，可以很方便地運用於臨床狀況。我們修改這個評分系統，讓這個簡化後的系統可以量化未接受腎臟移植、接受死亡器官捐贈移植或是活體捐贈移植病患的存活率。
　　
　　這個系統以169,393位罹患ESRD且適合接受器官捐贈患者進行，研究者們研發且確效一個多變項存活系統，用於預測死亡所需時間，且他們將其簡化成較單純的計分系統。
　　
　　該族群中將近有四分之一（23.5%）病患死亡。共有12個變項被確認為死亡率獨立預測因子：年齡、種族、腎臟衰竭原因、身體質量指數（BMI）、併存疾病、吸菸狀態、就業、血清白蛋白濃度、首次接受腎臟替代療法年代、腎臟移植、等待列到移植名單、以及在移植名單上等待時間長短。
　　
　　以這個指標系統，病患們被分為26組，其5年存活率變異性大，從最低風險組的97.78%到最高風險組的24.7%。在確效組的指標分數，一致性或然率為0.746（95%信賴區間為0.741-0.75），代表這是具有鑑別力的。對每個等級的指標分數，在研發與確效族群中，93.9%的觀察存活時間是相似的。
　　
　　試驗作者們寫到，我們的預後指標系統使用一般可獲得的資訊來正確地預測ESRD患者死亡率。這個指標系統可以提供臨床醫師們具價值的存活量化數據，也可以提供病患們決定是否接受移植，還是繼續接受透析。
　　
　　這項研究的限制包括缺乏考慮作為腎臟移植對象病患的應用性，當新的數據進來時，或許需要更新預後指標、以及這項模式缺乏捐贈者的特徵（除了活體或是死亡之外）。
　　
　　試驗作者們的結論是，最後，美國腎臟數據系統中有關共病的資訊可能是不完整的，且在這個模式中，僅有疾病是否存在的資訊，而非嚴重度。前瞻性地確效這個模式將會協助決定這樣的低估是否確實會發生。
　　
　　這項研究並未接受外在贊助。研究作者們表示已無相關資金上的往來。


New Clinical Index May Help Predict Mortality in Patients With End-Stage Renal Disease

By Laurie Barclay, MD
Medscape Medical News

April 7, 2010 — A new clinical prediction index may help evaluate the risk for mortality in patients with end-stage renal disease (ESRD) considering transplantation, according to the results of a study reported online March 29 in the Canadian Medical Association Journal.

"We aimed to derive and validate a new index to quantify survival accurately for the various treatment options facing a patient with ...ESRD," write Carl van Walraven, MD, MSc, from the University of Ottawa in Ontario, Canada, and colleagues. "We based this prognostic index on readily available data, so that it could be easily implemented in the clinical setting when transplantation-related counseling takes place. We modified this model into a simple scoring system to quantify survival without transplantation, with deceased-donor transplantation or with living-donor transplantation."

Using a population of 169,393 patients with ESRD who were eligible for transplantation, the investigators derived and validated a multivariable survival model predicting time to death, and they modified the model into a simple point-system index.

Nearly one quarter (23.5%) of the cohort died. There were 12 variables identified as independent predictors of mortality: age, race, cause of renal failure, body mass index (BMI), comorbid disease, smoking status, employment, serum albumin level, year of first renal replacement therapy, kidney transplantation, time to transplant wait-listing, and time on the wait list.

With use of the index, patients were separated into 26 groups with significantly varying 5-year survival duration, ranging from 97.8% in the lowest-risk group to 24.7% in the highest-risk group. Concordance probability of the index score in the validation group was 0.746 (95% confidence interval, 0.741 - 0.75), suggesting that it was highly discriminative. For each level of index score, observed survival duration in the derivation and validation cohorts was similar in 93.9% of patients.

"Our prognostic index uses commonly available information to predict mortality accurately in patients with ...ESRD," the study authors write. "This index could provide valuable quantitative data on survival for clinicians and patients to use when deciding whether to pursue transplantation or remain on dialysis."

Limitations of this study include lack of generalizability beyond patients who are considered to be candidates for renal transplantation, the need to update the prognostic index occasionally when new data become available, and lack of donor characteristics (other than living or deceased) in the model.

"Finally, information on comorbidities in the United States Renal Data System may be incompletely captured, and only the presence — not the severity — of the illness is accounted for in the model," the study authors conclude. "Hence, the impact of some comorbidities on survival may be underestimated by our model. Prospective validation of the model would help determine if this underestimation is indeed happening."

This study received no external funding. The study authors have disclosed no relevant financial relationships.

CMAJ. Published online March 29, 2010.