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估算妇科癌症患者卡铂给药剂量的肾小球滤过率。

Glomerular filtration rate estimation for carboplatin dosing in patients with gynaecological cancers.

机构信息

Department of Surgery and Cancer, Imperial College London, London, UK; Department of Medical Oncology, Imperial College Healthcare NHS Trust, London, UK. Electronic address: https://twitter.com/amit_samani1.

Department of Medical Oncology, Imperial College Healthcare NHS Trust, London, UK.

出版信息

ESMO Open. 2022 Apr;7(2):100401. doi: 10.1016/j.esmoop.2022.100401. Epub 2022 Feb 26.

DOI:10.1016/j.esmoop.2022.100401
PMID:35227967
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9058909/
Abstract

BACKGROUND

Carboplatin remains integral for treatment of gynaecological malignancies and dosing is based on glomerular filtration rate (GFR). Measurement via radiotracer decay [nuclear medicine GFR (nmGFR)] is ideal. However, this may be unavailable. Therefore GFR is often estimated using formulae that have not been validated in patients with cancer and/or specifically for gynaecological malignancies, leading to debate over optimal estimation. Suboptimal GFR estimation may affect efficacy or toxicity.

METHODS

We surveyed several UK National Health Service Trusts to assess carboplatin dosing practise. We then explored single-centre accuracy, bias and precision of various formulae for GFR estimation, relative to nmGFR, before validating our findings in an external cohort.

RESULTS

Across 18 Trusts, there was considerable heterogeneity in GFR estimation, including the formulae used [Cockcroft-Gault (CG) versus Wright], weight adjustment and area under the curve (AUC; 5 versus 6). We analysed 274 and 192 patients in two centres. Overall, CamGFR v2 (a novel formula for GFR estimation developed at Cambridge University Hospitals NHS Foundation Trust) excelled, showing the highest accuracy and precision. This translated into accuracy of hypothetical carboplatin dosing; nmGFR-derived carboplatin dose fell within 20% of the Cam GFR v2-derived dose in 86.5% and 87% of patients across the cohorts. Among the CG formula and its derivatives, using adjusted body weight in those with body mass index ≥25 kg/m [CG-adjusted body weight (CG-AdBW)] was optimal. The Wright and unadjusted CG estimators performed most poorly.

CONCLUSIONS

When compared with nmGFR assessment, accuracy, bias and precision varied widely between GFR estimators, with the newly developed Cam GFR v2 and CG-AdBW performing best. In general, weight (or body surface area)-adjusted formulae excelled, while the unadjusted CG and Wright formulae or the use of AUC6 (versus nmGFR AUC5) produced risk of significant overdose. Thus, individual centres should validate their GFR estimation methods. In the absence of validation, CG-AdBW or CamGFR v2 is likely to perform well while unadjusted CG/Wright formulae or AUC6 dosing should be avoided.

摘要

背景

卡铂仍然是妇科恶性肿瘤治疗的重要组成部分,剂量基于肾小球滤过率(GFR)。使用放射性示踪剂衰变(核医学 GFR(nmGFR))进行测量是理想的。然而,这可能无法实现。因此,GFR 通常使用未经癌症患者验证且/或专门针对妇科恶性肿瘤的公式进行估算,这导致了关于最佳估算方法的争议。GFR 估算不当可能会影响疗效或毒性。

方法

我们调查了几家英国国民保健服务信托基金,以评估卡铂给药实践。然后,我们在一个外部队列中验证了我们的发现之前,探索了各种 GFR 估算公式相对于 nmGFR 的准确性、偏差和精密度。

结果

在 18 家信托基金中,GFR 估算存在相当大的异质性,包括使用的公式( Cockcroft-Gault [CG] 与 Wright)、体重调整和曲线下面积(AUC;5 与 6)。我们在两个中心分析了 274 名和 192 名患者。总体而言,CamGFR v2(剑桥大学医院 NHS 基金会信托基金开发的一种新的 GFR 估算公式)表现出色,显示出最高的准确性和精密度。这转化为假设的卡铂给药剂量的准确性;nmGFR 衍生的卡铂剂量在两个队列中的 86.5%和 87%的患者中落在 CamGFR v2 衍生剂量的 20%以内。在 CG 公式及其衍生物中,对于 BMI≥25kg/m2 的患者,使用调整后的体重(CG 调整体重(CG-AdBW))是最佳的。Wright 和未调整的 CG 估算器表现最差。

结论

与 nmGFR 评估相比,GFR 估算之间的准确性、偏差和精密度差异很大,新开发的 CamGFR v2 和 CG-AdBW 表现最佳。一般来说,体重(或体表面积)调整公式表现出色,而未调整的 CG 和 Wright 公式或 AUC6(与 nmGFR AUC5 相比)给药可能会导致严重过量的风险。因此,各个中心应验证其 GFR 估算方法。在缺乏验证的情况下,CG-AdBW 或 CamGFR v2 可能表现良好,而未调整的 CG/Wright 公式或 AUC6 给药应避免使用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f463/9058909/14a8d981d128/figs8.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f463/9058909/cfddebe98361/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f463/9058909/51d5763c24b7/gr2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f463/9058909/8ef23b88d1c2/figs1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f463/9058909/0cafafe3e2b8/figs2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f463/9058909/6278201aa777/figs3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f463/9058909/937b7d59d6cf/figs4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f463/9058909/fcdb685874ba/figs5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f463/9058909/f4ebabf56d2a/figs6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f463/9058909/9475adada739/figs7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f463/9058909/14a8d981d128/figs8.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f463/9058909/cfddebe98361/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f463/9058909/51d5763c24b7/gr2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f463/9058909/8ef23b88d1c2/figs1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f463/9058909/0cafafe3e2b8/figs2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f463/9058909/6278201aa777/figs3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f463/9058909/937b7d59d6cf/figs4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f463/9058909/fcdb685874ba/figs5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f463/9058909/f4ebabf56d2a/figs6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f463/9058909/9475adada739/figs7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f463/9058909/14a8d981d128/figs8.jpg

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