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A prognostic nomogram to predict overall survival in patients with platinum-sensitive recurrent ovarian cancer

Identifieur interne : 005131 ( Main/Exploration ); précédent : 005130; suivant : 005132

A prognostic nomogram to predict overall survival in patients with platinum-sensitive recurrent ovarian cancer

Auteurs : C. K. Lee [Australie] ; R. J. Simes [Australie] ; C. Brown [Australie] ; V. Gebski [Australie] ; J. Pfisterer [Allemagne] ; A.-M. Swart [Royaume-Uni] ; D. Berton-Rigaud [France] ; M. Plante [Canada] ; T. Skeie-Jensen [Norvège] ; I. Vergote [Belgique] ; C. Schauer [Autriche] ; C. Pisano [Italie] ; G. Parma [Italie] ; K. Baumann [Allemagne] ; J. A. Ledermann [Royaume-Uni] ; E. Pujade-Lauraine [France] ; J. Bentley [Canada] ; G. Kristensen [Norvège] ; A. Belau [Allemagne] ; M. Nankivell [Royaume-Uni] ; U. Canzler [Allemagne] ; S. J. Lord [Australie] ; C. Kurzeder [Allemagne] ; M. Friedlander [Australie]

Source :

RBID : Pascal:13-0150991

Descripteurs français

English descriptors

Abstract

Background: Patients with platinum-sensitive recurrent ovarian cancer have variable prognosis and survival. We extend previous work on prediction of progression-free survival by developing a nomogram to predict overall survival (OS) in these patients treated with platinum-based chemotherapy. Patients and methods: The nomogram was developed using data from the CAELYX in Platinum-Sensitive Ovarian Patients (CALYPSO) trial. Multivariate proportional hazards models were generated based on pre-treatment characteristics to develop a nomogram that classifies patient prognosis based on OS outcome. We also developed two simpler models with fewer variables and conducted model validations in independent datasets from AGO-OVAR Study 2.5 and ICON 4. We compare the performance of the nomogram with the simpler models by examining the differences in the C-statistics and net reclassification index (NRI). Results: The nomogram included six significant predictors: interval from last platinum chemotherapy, performance status, size of the largest tumour, CA-125, haemoglobin and the number of organ sites of metastasis (C-statistic 0.67; 95% confidence interval 0.65-0.69). Among the CALPYSO patients, the median OS for good, intermediate and poor prognosis groups was 56.2, 31.0 and 20.8 months, respectively. When CA-125 was not included in the model, the C-statistics were 0.65 (CALYPSO) and 0.64 (AGO-OVAR 2.5). A simpler model (interval from last platinum chemotherapy, performance status and CA-125) produced a significant decrease of the C-statistic (0.63) and NRI (26.4%, P < 0.0001). Conclusions: This nomogram with six pre-treatment characteristics improves OS prediction in patients with platinum-sensitive ovarian cancer and is superior to models with fewer prognostic factors or platinum chemotherapy free interval alone. With independent validation, this nomogram could potentially be useful for improved stratification of patients in clinical trials and also for counselling patients.


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Le document en format XML

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<title xml:lang="en" level="a">A prognostic nomogram to predict overall survival in patients with platinum-sensitive recurrent ovarian cancer</title>
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<settlement type="city">Sydney</settlement>
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<country>Autriche</country>
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<author>
<name sortKey="Pisano, C" sort="Pisano, C" uniqKey="Pisano C" first="C." last="Pisano">C. Pisano</name>
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<s1>Division of Medical Oncology, Uro-Gynecological Department, National Cancer Institute of Naples</s1>
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</inist:fA14>
<country>Italie</country>
<wicri:noRegion>Napoli</wicri:noRegion>
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<name sortKey="Parma, G" sort="Parma, G" uniqKey="Parma G" first="G." last="Parma">G. Parma</name>
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<s2>Milan</s2>
<s3>ITA</s3>
<sZ>13 aut.</sZ>
</inist:fA14>
<country>Italie</country>
<placeName>
<settlement type="city">Milan</settlement>
<region nuts="2">Lombardie</region>
</placeName>
</affiliation>
</author>
<author>
<name sortKey="Baumann, K" sort="Baumann, K" uniqKey="Baumann K" first="K." last="Baumann">K. Baumann</name>
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<s3>DEU</s3>
<sZ>14 aut.</sZ>
</inist:fA14>
<country>Allemagne</country>
<placeName>
<region type="land" nuts="1">Hesse (Land)</region>
<region type="district" nuts="2">District de Giessen</region>
<settlement type="city">Marbourg</settlement>
</placeName>
</affiliation>
</author>
<author>
<name sortKey="Ledermann, J A" sort="Ledermann, J A" uniqKey="Ledermann J" first="J. A." last="Ledermann">J. A. Ledermann</name>
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<inist:fA14 i1="12">
<s1>UCL and UCLH Biomedical Research Centre, UCL Cancer Institute</s1>
<s2>London</s2>
<s3>GBR</s3>
<sZ>15 aut.</sZ>
</inist:fA14>
<country>Royaume-Uni</country>
<placeName>
<settlement type="city">Londres</settlement>
<region type="country">Angleterre</region>
<region type="région" nuts="1">Grand Londres</region>
</placeName>
</affiliation>
</author>
<author>
<name sortKey="Pujade Lauraine, E" sort="Pujade Lauraine, E" uniqKey="Pujade Lauraine E" first="E." last="Pujade-Lauraine">E. Pujade-Lauraine</name>
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<s1>University Paris Descartes, Assistance Publique-Hôpitaux de Paris, Hôpital Hotel-Dieu</s1>
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<sZ>16 aut.</sZ>
</inist:fA14>
<country>France</country>
<placeName>
<region type="region">Île-de-France</region>
<region type="old region">Île-de-France</region>
<settlement type="city">Paris</settlement>
</placeName>
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<name sortKey="Bentley, J" sort="Bentley, J" uniqKey="Bentley J" first="J." last="Bentley">J. Bentley</name>
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<sZ>18 aut.</sZ>
</inist:fA14>
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<sZ>19 aut.</sZ>
</inist:fA14>
<country>Allemagne</country>
<wicri:noRegion>Greifswald</wicri:noRegion>
<wicri:noRegion>Ernst Moritz Arndt University</wicri:noRegion>
<wicri:noRegion>Greifswald</wicri:noRegion>
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<name sortKey="Nankivell, M" sort="Nankivell, M" uniqKey="Nankivell M" first="M." last="Nankivell">M. Nankivell</name>
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<sZ>20 aut.</sZ>
</inist:fA14>
<country>Royaume-Uni</country>
<placeName>
<settlement type="city">Londres</settlement>
<region type="country">Angleterre</region>
<region type="région" nuts="1">Grand Londres</region>
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</affiliation>
</author>
<author>
<name sortKey="Canzler, U" sort="Canzler, U" uniqKey="Canzler U" first="U." last="Canzler">U. Canzler</name>
<affiliation wicri:level="3">
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<s1>Department of Obstetrics and Gynecology, University Hospital Carl Gustav Carus</s1>
<s2>Dresden</s2>
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<sZ>21 aut.</sZ>
</inist:fA14>
<country>Allemagne</country>
<placeName>
<region type="land" nuts="1">Saxe (Land)</region>
<region type="district" nuts="2">District de Dresde</region>
<settlement type="city">Dresde</settlement>
</placeName>
</affiliation>
</author>
<author>
<name sortKey="Lord, S J" sort="Lord, S J" uniqKey="Lord S" first="S. J." last="Lord">S. J. Lord</name>
<affiliation wicri:level="4">
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<country>Australie</country>
<placeName>
<settlement type="city">Sydney</settlement>
<region type="état">Nouvelle-Galles du Sud</region>
<settlement type="city">Sydney</settlement>
</placeName>
<orgName type="university">Université de Sydney</orgName>
</affiliation>
</author>
<author>
<name sortKey="Kurzeder, C" sort="Kurzeder, C" uniqKey="Kurzeder C" first="C." last="Kurzeder">C. Kurzeder</name>
<affiliation wicri:level="1">
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<author>
<name sortKey="Friedlander, M" sort="Friedlander, M" uniqKey="Friedlander M" first="M." last="Friedlander">M. Friedlander</name>
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<s1>Department of Medical Oncology, Prince of Wales Hospital</s1>
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</inist:fA14>
<country>Australie</country>
<placeName>
<settlement type="city">Sydney</settlement>
<region type="état">Nouvelle-Galles du Sud</region>
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</analytic>
<series>
<title level="j" type="main">Annals of oncology</title>
<title level="j" type="abbreviated">Ann. oncol.</title>
<idno type="ISSN">0923-7534</idno>
<imprint>
<date when="2013">2013</date>
</imprint>
</series>
</biblStruct>
</sourceDesc>
<seriesStmt>
<title level="j" type="main">Annals of oncology</title>
<title level="j" type="abbreviated">Ann. oncol.</title>
<idno type="ISSN">0923-7534</idno>
</seriesStmt>
</fileDesc>
<profileDesc>
<textClass>
<keywords scheme="KwdEn" xml:lang="en">
<term>Human</term>
<term>Nomogram</term>
<term>Ovary cancer</term>
<term>Patient</term>
<term>Platinum</term>
<term>Predictive factor</term>
<term>Prognosis</term>
<term>Relapse</term>
<term>Sensitivity</term>
<term>Survival</term>
</keywords>
<keywords scheme="Pascal" xml:lang="fr">
<term>Pronostic</term>
<term>Nomogramme</term>
<term>Facteur prédictif</term>
<term>Survie</term>
<term>Homme</term>
<term>Malade</term>
<term>Platine</term>
<term>Récidive</term>
<term>Cancer de l'ovaire</term>
<term>Sensibilité</term>
</keywords>
<keywords scheme="Wicri" type="topic" xml:lang="fr">
<term>Homme</term>
<term>Platine</term>
</keywords>
</textClass>
</profileDesc>
</teiHeader>
<front>
<div type="abstract" xml:lang="en">Background: Patients with platinum-sensitive recurrent ovarian cancer have variable prognosis and survival. We extend previous work on prediction of progression-free survival by developing a nomogram to predict overall survival (OS) in these patients treated with platinum-based chemotherapy. Patients and methods: The nomogram was developed using data from the CAELYX in Platinum-Sensitive Ovarian Patients (CALYPSO) trial. Multivariate proportional hazards models were generated based on pre-treatment characteristics to develop a nomogram that classifies patient prognosis based on OS outcome. We also developed two simpler models with fewer variables and conducted model validations in independent datasets from AGO-OVAR Study 2.5 and ICON 4. We compare the performance of the nomogram with the simpler models by examining the differences in the C-statistics and net reclassification index (NRI). Results: The nomogram included six significant predictors: interval from last platinum chemotherapy, performance status, size of the largest tumour, CA-125, haemoglobin and the number of organ sites of metastasis (C-statistic 0.67; 95% confidence interval 0.65-0.69). Among the CALPYSO patients, the median OS for good, intermediate and poor prognosis groups was 56.2, 31.0 and 20.8 months, respectively. When CA-125 was not included in the model, the C-statistics were 0.65 (CALYPSO) and 0.64 (AGO-OVAR 2.5). A simpler model (interval from last platinum chemotherapy, performance status and CA-125) produced a significant decrease of the C-statistic (0.63) and NRI (26.4%, P < 0.0001). Conclusions: This nomogram with six pre-treatment characteristics improves OS prediction in patients with platinum-sensitive ovarian cancer and is superior to models with fewer prognostic factors or platinum chemotherapy free interval alone. With independent validation, this nomogram could potentially be useful for improved stratification of patients in clinical trials and also for counselling patients.</div>
</front>
</TEI>
<affiliations>
<list>
<country>
<li>Allemagne</li>
<li>Australie</li>
<li>Autriche</li>
<li>Belgique</li>
<li>Canada</li>
<li>France</li>
<li>Italie</li>
<li>Norvège</li>
<li>Royaume-Uni</li>
</country>
<region>
<li>Angleterre</li>
<li>District de Dresde</li>
<li>District de Giessen</li>
<li>Grand Londres</li>
<li>Hesse (Land)</li>
<li>Lombardie</li>
<li>Nouvelle-Galles du Sud</li>
<li>Saxe (Land)</li>
<li>Schleswig-Holstein</li>
<li>Île-de-France</li>
<li>Østlandet</li>
</region>
<settlement>
<li>Dresde</li>
<li>Kiel</li>
<li>Londres</li>
<li>Marbourg</li>
<li>Milan</li>
<li>Oslo</li>
<li>Paris</li>
<li>Sydney</li>
</settlement>
<orgName>
<li>Université de Sydney</li>
</orgName>
</list>
<tree>
<country name="Australie">
<region name="Nouvelle-Galles du Sud">
<name sortKey="Lee, C K" sort="Lee, C K" uniqKey="Lee C" first="C. K." last="Lee">C. K. Lee</name>
</region>
<name sortKey="Brown, C" sort="Brown, C" uniqKey="Brown C" first="C." last="Brown">C. Brown</name>
<name sortKey="Friedlander, M" sort="Friedlander, M" uniqKey="Friedlander M" first="M." last="Friedlander">M. Friedlander</name>
<name sortKey="Gebski, V" sort="Gebski, V" uniqKey="Gebski V" first="V." last="Gebski">V. Gebski</name>
<name sortKey="Lord, S J" sort="Lord, S J" uniqKey="Lord S" first="S. J." last="Lord">S. J. Lord</name>
<name sortKey="Simes, R J" sort="Simes, R J" uniqKey="Simes R" first="R. J." last="Simes">R. J. Simes</name>
</country>
<country name="Allemagne">
<region name="Schleswig-Holstein">
<name sortKey="Pfisterer, J" sort="Pfisterer, J" uniqKey="Pfisterer J" first="J." last="Pfisterer">J. Pfisterer</name>
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<name sortKey="Baumann, K" sort="Baumann, K" uniqKey="Baumann K" first="K." last="Baumann">K. Baumann</name>
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<name sortKey="Canzler, U" sort="Canzler, U" uniqKey="Canzler U" first="U." last="Canzler">U. Canzler</name>
<name sortKey="Kurzeder, C" sort="Kurzeder, C" uniqKey="Kurzeder C" first="C." last="Kurzeder">C. Kurzeder</name>
</country>
<country name="Royaume-Uni">
<region name="Angleterre">
<name sortKey="Swart, A M" sort="Swart, A M" uniqKey="Swart A" first="A.-M." last="Swart">A.-M. Swart</name>
</region>
<name sortKey="Ledermann, J A" sort="Ledermann, J A" uniqKey="Ledermann J" first="J. A." last="Ledermann">J. A. Ledermann</name>
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<name sortKey="Berton Rigaud, D" sort="Berton Rigaud, D" uniqKey="Berton Rigaud D" first="D." last="Berton-Rigaud">D. Berton-Rigaud</name>
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<name sortKey="Pujade Lauraine, E" sort="Pujade Lauraine, E" uniqKey="Pujade Lauraine E" first="E." last="Pujade-Lauraine">E. Pujade-Lauraine</name>
</country>
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<noRegion>
<name sortKey="Plante, M" sort="Plante, M" uniqKey="Plante M" first="M." last="Plante">M. Plante</name>
</noRegion>
<name sortKey="Bentley, J" sort="Bentley, J" uniqKey="Bentley J" first="J." last="Bentley">J. Bentley</name>
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<name sortKey="Skeie Jensen, T" sort="Skeie Jensen, T" uniqKey="Skeie Jensen T" first="T." last="Skeie-Jensen">T. Skeie-Jensen</name>
</region>
<name sortKey="Kristensen, G" sort="Kristensen, G" uniqKey="Kristensen G" first="G." last="Kristensen">G. Kristensen</name>
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<name sortKey="Schauer, C" sort="Schauer, C" uniqKey="Schauer C" first="C." last="Schauer">C. Schauer</name>
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<name sortKey="Pisano, C" sort="Pisano, C" uniqKey="Pisano C" first="C." last="Pisano">C. Pisano</name>
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<name sortKey="Parma, G" sort="Parma, G" uniqKey="Parma G" first="G." last="Parma">G. Parma</name>
</country>
</tree>
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</record>

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