Risk prediction model for disease-free survival in women with early-stage cervical cancers following postoperative (chemo)radiotherapy

Hyoung Uk Je, Seungbong Han, Young Seok Kim, Joo Hyun Nam, Won Park, Sanghyuk Song, Changhoon Song, Jin Hee Kim, Juree Kim, Won Sup Yoon, Mee Sun Yoon, Hwa Jin Choi, Joo Young Kim

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

PURPOSE: To investigate disease-free survival (DFS) and prognostic factors following the administration of postoperative (chemo)radiotherapy in patients with early-stage cervical cancers.

METHODS: The medical records of 1,069 patients from 10 participating institutions were reviewed. Statistically and clinically established factors were considered as candidates for constructing the prediction model. This model was validated, using bootstrapping to correct for optimistic bias.

RESULTS: The 5-year DFS rate was 81.1%, with a median follow-up period of 59.6 months. The statistically significant prognostic factors were as follows: pelvic lymph node metastasis, histologic type, parametrial invasion, lymphovascular space invasion, and tumor size. The nomogram for DFS was constructed, and it demonstrated a good discrimination performance, with an internally validated concordance index of 0.72.

CONCLUSIONS: Our predictive model exhibited accurate predictions and may be useful in designing clinical trials to study if further chemotherapy can reduce the recurrence of disease in high-risk patients.

Original languageEnglish
Pages (from-to)105-110
Number of pages6
JournalTumori
Volume104
Issue number2
DOIs
Publication statusPublished - 2018 Mar 1

Fingerprint

Uterine Cervical Neoplasms
Disease-Free Survival
Radiotherapy
Nomograms
Medical Records
Survival Rate
Lymph Nodes
Clinical Trials
Neoplasm Metastasis
Recurrence
Drug Therapy
Neoplasms

Keywords

  • Adjuvant radiation therapy
  • Disease-free survival
  • Uterine cervical cancer

ASJC Scopus subject areas

  • Oncology
  • Cancer Research

Cite this

Risk prediction model for disease-free survival in women with early-stage cervical cancers following postoperative (chemo)radiotherapy. / Je, Hyoung Uk; Han, Seungbong; Kim, Young Seok; Nam, Joo Hyun; Park, Won; Song, Sanghyuk; Song, Changhoon; Kim, Jin Hee; Kim, Juree; Yoon, Won Sup; Yoon, Mee Sun; Choi, Hwa Jin; Kim, Joo Young.

In: Tumori, Vol. 104, No. 2, 01.03.2018, p. 105-110.

Research output: Contribution to journalArticle

Je, HU, Han, S, Kim, YS, Nam, JH, Park, W, Song, S, Song, C, Kim, JH, Kim, J, Yoon, WS, Yoon, MS, Choi, HJ & Kim, JY 2018, 'Risk prediction model for disease-free survival in women with early-stage cervical cancers following postoperative (chemo)radiotherapy', Tumori, vol. 104, no. 2, pp. 105-110. https://doi.org/10.5301/tj.5000697
Je, Hyoung Uk ; Han, Seungbong ; Kim, Young Seok ; Nam, Joo Hyun ; Park, Won ; Song, Sanghyuk ; Song, Changhoon ; Kim, Jin Hee ; Kim, Juree ; Yoon, Won Sup ; Yoon, Mee Sun ; Choi, Hwa Jin ; Kim, Joo Young. / Risk prediction model for disease-free survival in women with early-stage cervical cancers following postoperative (chemo)radiotherapy. In: Tumori. 2018 ; Vol. 104, No. 2. pp. 105-110.
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AU - Song, Sanghyuk

AU - Song, Changhoon

AU - Kim, Jin Hee

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AB - PURPOSE: To investigate disease-free survival (DFS) and prognostic factors following the administration of postoperative (chemo)radiotherapy in patients with early-stage cervical cancers.METHODS: The medical records of 1,069 patients from 10 participating institutions were reviewed. Statistically and clinically established factors were considered as candidates for constructing the prediction model. This model was validated, using bootstrapping to correct for optimistic bias.RESULTS: The 5-year DFS rate was 81.1%, with a median follow-up period of 59.6 months. The statistically significant prognostic factors were as follows: pelvic lymph node metastasis, histologic type, parametrial invasion, lymphovascular space invasion, and tumor size. The nomogram for DFS was constructed, and it demonstrated a good discrimination performance, with an internally validated concordance index of 0.72.CONCLUSIONS: Our predictive model exhibited accurate predictions and may be useful in designing clinical trials to study if further chemotherapy can reduce the recurrence of disease in high-risk patients.

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