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Clinical Colorectal Cancer 2007-Jan

Severe diarrhea in patients with advanced-stage colorectal cancer receiving FOLFOX or FOLFIRI chemotherapy: the development of a risk prediction tool.

يمكن للمستخدمين المسجلين فقط ترجمة المقالات
الدخول التسجيل فى الموقع
يتم حفظ الارتباط في الحافظة
George Dranitsaris
Amil Shah
Biljana Spirovski
Mark Vincent

الكلمات الدالة

نبذة مختصرة

BACKGROUND

FOLFOX (oxaliplatin/leucovorin/5-fluorouracil) and FOLFIRI (irinotecan/leucovorin/5-fluorouracil) are important regimens for the treatment of advanced-stage colorectal cancer (CRC). However, both are associated with severe diarrhea, leading to hospitalization, dose reductions/delays, and even death. In this study, the development of a prediction model for severe diarrhea is described.

METHODS

The records of 200 patients with CRC who had received FOLFOX or FOLFIRI in 3 Canadian cancer centers were reviewed. Clinical and biochemistry parameters potentially associated with diarrhea were abstracted. Logistic regression analysis was applied to develop the final risk model. A risk scoring system, ranging from 0 to 15, was then created from the regression parameters. A receiver operative characteristic curve analysis was done to measure the accuracy of the scoring system.

RESULTS

Important predictors for severe diarrhea included existing comorbidity, patient performance status, an increased baseline bilirubin level, resection of the primary tumor, FOLFOX chemotherapy, metastatic or advanced locoregional versus resected stage IV disease, and the initiation of treatment in the summer months. The receiver operative characteristic analysis had an area under the curve of 0.80 (95% confidence interval, 0.74-0.87). An overall risk score of > or = 7 for a given patient was identified as being the optimal cutoff to maximize the sensitivity (61.4%) and specificity (89.6%) of the prediction tool.

CONCLUSIONS

We developed a prediction tool for severe diarrhea in patients with CRC receiving FOLFOX or FOLFIRI chemotherapy. To make the model available for easy use and access, we have incorporated it on to our risk prediction Web site: www.PredictPatientEvents.com. Prospective external validation is also being planned.

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قاعدة بيانات الأعشاب الطبية الأكثر اكتمالا التي يدعمها العلم

  • يعمل في 55 لغة
  • العلاجات العشبية مدعومة بالعلم
  • التعرف على الأعشاب بالصورة
  • خريطة GPS تفاعلية - ضع علامة على الأعشاب في الموقع (قريبًا)
  • اقرأ المنشورات العلمية المتعلقة ببحثك
  • البحث عن الأعشاب الطبية من آثارها
  • نظّم اهتماماتك وابقَ على اطلاع دائم بأبحاث الأخبار والتجارب السريرية وبراءات الاختراع

اكتب أحد الأعراض أو المرض واقرأ عن الأعشاب التي قد تساعد ، واكتب عشبًا واطلع على الأمراض والأعراض التي تستخدم ضدها.
* تستند جميع المعلومات إلى البحوث العلمية المنشورة

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