The need for preoperative baseline arm measurement to accurately quantify breast cancer-related lymphedema.
Identifieur interne : 000842 ( PubMed/Curation ); précédent : 000841; suivant : 000843The need for preoperative baseline arm measurement to accurately quantify breast cancer-related lymphedema.
Auteurs : Fangdi Sun [États-Unis] ; Melissa N. Skolny [États-Unis] ; Meyha N. Swaroop [États-Unis] ; Bhupendra Rawal [États-Unis] ; Paul J. Catalano [États-Unis] ; Cheryl L. Brunelle [États-Unis] ; Cynthia L. Miller [États-Unis] ; Alphonse G. Taghian [États-Unis]Source :
- Breast cancer research and treatment [ 1573-7217 ] ; 2016.
Abstract
Breast cancer-related lymphedema (BCRL) is a feared outcome of breast cancer treatment, yet the push for early screening is hampered by a lack of standardized quantification. We sought to determine the necessity of preoperative baseline in accounting for temporal changes of upper extremity volume. 1028 women with unilateral breast cancer were prospectively screened for lymphedema by perometry. Thresholds were defined: relative volume change (RVC) ≥10 % for clinically significant lymphedema and ≥5 % including subclinical lymphedema. The first postoperative measurement (pseudo-baseline) simulated the case of no baseline. McNemar's test and binomial logistic regression models were used to analyze BCRL misdiagnoses. Preoperatively, 28.3 and 2.9 % of patients had arm asymmetry of ≥5 and 10 %, respectively. Without baseline, 41.6 % of patients were underdiagnosed and 40.1 % overdiagnosed at RVC ≥ 5 %, increasing to 50.0 and 54.8 % at RVC ≥ 10 %. Increased pseudo-baseline asymmetry, increased weight change between baselines, hormonal therapy, dominant use of contralateral arm, and not receiving axillary lymph node dissection (ALND) were associated with increased risk of underdiagnosis at RVC ≥ 5 %; not receiving regional lymph node radiation was significant at RVC ≥ 10 %. Increased pseudo-baseline asymmetry, not receiving ALND, and dominant use of ipsilateral arm were associated with overdiagnosis at RVC ≥ 5 %; increased pseudo-baseline asymmetry and not receiving ALND were significant at RVC ≥ 10 %. The use of a postoperative proxy even early after treatment results in poor sensitivity for identifying BCRL. Providers with access to patients before surgery should consider the consequent need for proper baseline, with specific strategy tailored by institution.
DOI: 10.1007/s10549-016-3821-0
PubMed: 27154787
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Skolny</name><affiliation wicri:level="1"><nlm:affiliation>Department of Radiation Oncology, Massachusetts General Hospital, Harvard Medical School, 100 Blossom Street, Boston, MA, 02114, USA.</nlm:affiliation><country xml:lang="fr">États-Unis</country><wicri:regionArea>Department of Radiation Oncology, Massachusetts General Hospital, Harvard Medical School, 100 Blossom Street, Boston, MA, 02114</wicri:regionArea></affiliation></author><author><name sortKey="Swaroop, Meyha N" sort="Swaroop, Meyha N" uniqKey="Swaroop M" first="Meyha N" last="Swaroop">Meyha N. Swaroop</name><affiliation wicri:level="1"><nlm:affiliation>Department of Radiation Oncology, Massachusetts General Hospital, Harvard Medical School, 100 Blossom Street, Boston, MA, 02114, USA.</nlm:affiliation><country xml:lang="fr">États-Unis</country><wicri:regionArea>Department of Radiation Oncology, Massachusetts General Hospital, Harvard Medical School, 100 Blossom Street, Boston, MA, 02114</wicri:regionArea></affiliation></author><author><name sortKey="Rawal, Bhupendra" sort="Rawal, Bhupendra" uniqKey="Rawal B" first="Bhupendra" last="Rawal">Bhupendra Rawal</name><affiliation wicri:level="1"><nlm:affiliation>Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, 450 Brookline Avenue, Boston, MA, 02115, USA.</nlm:affiliation><country xml:lang="fr">États-Unis</country><wicri:regionArea>Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, 450 Brookline Avenue, Boston, MA, 02115</wicri:regionArea></affiliation></author><author><name sortKey="Catalano, Paul J" sort="Catalano, Paul J" uniqKey="Catalano P" first="Paul J" last="Catalano">Paul J. Catalano</name><affiliation wicri:level="1"><nlm:affiliation>Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, 450 Brookline Avenue, Boston, MA, 02115, USA.</nlm:affiliation><country xml:lang="fr">États-Unis</country><wicri:regionArea>Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, 450 Brookline Avenue, Boston, MA, 02115</wicri:regionArea></affiliation></author><author><name sortKey="Brunelle, Cheryl L" sort="Brunelle, Cheryl L" uniqKey="Brunelle C" first="Cheryl L" last="Brunelle">Cheryl L. Brunelle</name><affiliation wicri:level="1"><nlm:affiliation>Department of Physical and Occupational Therapy, Massachusetts General Hospital, Harvard Medical School, 100 Blossom Street, Boston, MA, 02114, USA.</nlm:affiliation><country xml:lang="fr">États-Unis</country><wicri:regionArea>Department of Physical and Occupational Therapy, Massachusetts General Hospital, Harvard Medical School, 100 Blossom Street, Boston, MA, 02114</wicri:regionArea></affiliation></author><author><name sortKey="Miller, Cynthia L" sort="Miller, Cynthia L" uniqKey="Miller C" first="Cynthia L" last="Miller">Cynthia L. Miller</name><affiliation wicri:level="1"><nlm:affiliation>Department of Radiation Oncology, Massachusetts General Hospital, Harvard Medical School, 100 Blossom Street, Boston, MA, 02114, USA.</nlm:affiliation><country xml:lang="fr">États-Unis</country><wicri:regionArea>Department of Radiation Oncology, Massachusetts General Hospital, Harvard Medical School, 100 Blossom Street, Boston, MA, 02114</wicri:regionArea></affiliation></author><author><name sortKey="Taghian, Alphonse G" sort="Taghian, Alphonse G" uniqKey="Taghian A" first="Alphonse G" last="Taghian">Alphonse G. Taghian</name><affiliation wicri:level="1"><nlm:affiliation>Department of Radiation Oncology, Massachusetts General Hospital, Harvard Medical School, 100 Blossom Street, Boston, MA, 02114, USA. ataghian@partners.org.</nlm:affiliation><country xml:lang="fr">États-Unis</country><wicri:regionArea>Department of Radiation Oncology, Massachusetts General Hospital, Harvard Medical School, 100 Blossom Street, Boston, MA, 02114</wicri:regionArea></affiliation></author></analytic><series><title level="j">Breast cancer research and treatment</title><idno type="eISSN">1573-7217</idno><imprint><date when="2016" type="published">2016</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">Breast cancer-related lymphedema (BCRL) is a feared outcome of breast cancer treatment, yet the push for early screening is hampered by a lack of standardized quantification. We sought to determine the necessity of preoperative baseline in accounting for temporal changes of upper extremity volume. 1028 women with unilateral breast cancer were prospectively screened for lymphedema by perometry. Thresholds were defined: relative volume change (RVC) ≥10 % for clinically significant lymphedema and ≥5 % including subclinical lymphedema. The first postoperative measurement (pseudo-baseline) simulated the case of no baseline. McNemar's test and binomial logistic regression models were used to analyze BCRL misdiagnoses. Preoperatively, 28.3 and 2.9 % of patients had arm asymmetry of ≥5 and 10 %, respectively. Without baseline, 41.6 % of patients were underdiagnosed and 40.1 % overdiagnosed at RVC ≥ 5 %, increasing to 50.0 and 54.8 % at RVC ≥ 10 %. Increased pseudo-baseline asymmetry, increased weight change between baselines, hormonal therapy, dominant use of contralateral arm, and not receiving axillary lymph node dissection (ALND) were associated with increased risk of underdiagnosis at RVC ≥ 5 %; not receiving regional lymph node radiation was significant at RVC ≥ 10 %. Increased pseudo-baseline asymmetry, not receiving ALND, and dominant use of ipsilateral arm were associated with overdiagnosis at RVC ≥ 5 %; increased pseudo-baseline asymmetry and not receiving ALND were significant at RVC ≥ 10 %. The use of a postoperative proxy even early after treatment results in poor sensitivity for identifying BCRL. Providers with access to patients before surgery should consider the consequent need for proper baseline, with specific strategy tailored by institution.</div></front></TEI><pubmed><MedlineCitation Status="In-Process" Owner="NLM"><PMID Version="1">27154787</PMID><DateCreated><Year>2016</Year><Month>05</Month><Day>21</Day></DateCreated><DateRevised><Year>2017</Year><Month>04</Month><Day>25</Day></DateRevised><Article PubModel="Print-Electronic"><Journal><ISSN IssnType="Electronic">1573-7217</ISSN><JournalIssue CitedMedium="Internet"><Volume>157</Volume><Issue>2</Issue><PubDate><Year>2016</Year><Month>Jun</Month></PubDate></JournalIssue><Title>Breast cancer research and treatment</Title><ISOAbbreviation>Breast Cancer Res. Treat.</ISOAbbreviation></Journal><ArticleTitle>The need for preoperative baseline arm measurement to accurately quantify breast cancer-related lymphedema.</ArticleTitle><Pagination><MedlinePgn>229-240</MedlinePgn></Pagination><ELocationID EIdType="doi" ValidYN="Y">10.1007/s10549-016-3821-0</ELocationID><Abstract><AbstractText>Breast cancer-related lymphedema (BCRL) is a feared outcome of breast cancer treatment, yet the push for early screening is hampered by a lack of standardized quantification. We sought to determine the necessity of preoperative baseline in accounting for temporal changes of upper extremity volume. 1028 women with unilateral breast cancer were prospectively screened for lymphedema by perometry. Thresholds were defined: relative volume change (RVC) ≥10 % for clinically significant lymphedema and ≥5 % including subclinical lymphedema. The first postoperative measurement (pseudo-baseline) simulated the case of no baseline. McNemar's test and binomial logistic regression models were used to analyze BCRL misdiagnoses. Preoperatively, 28.3 and 2.9 % of patients had arm asymmetry of ≥5 and 10 %, respectively. Without baseline, 41.6 % of patients were underdiagnosed and 40.1 % overdiagnosed at RVC ≥ 5 %, increasing to 50.0 and 54.8 % at RVC ≥ 10 %. Increased pseudo-baseline asymmetry, increased weight change between baselines, hormonal therapy, dominant use of contralateral arm, and not receiving axillary lymph node dissection (ALND) were associated with increased risk of underdiagnosis at RVC ≥ 5 %; not receiving regional lymph node radiation was significant at RVC ≥ 10 %. Increased pseudo-baseline asymmetry, not receiving ALND, and dominant use of ipsilateral arm were associated with overdiagnosis at RVC ≥ 5 %; increased pseudo-baseline asymmetry and not receiving ALND were significant at RVC ≥ 10 %. The use of a postoperative proxy even early after treatment results in poor sensitivity for identifying BCRL. Providers with access to patients before surgery should consider the consequent need for proper baseline, with specific strategy tailored by institution.</AbstractText></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Sun</LastName><ForeName>Fangdi</ForeName><Initials>F</Initials><AffiliationInfo><Affiliation>Department of Radiation Oncology, Massachusetts General Hospital, Harvard Medical School, 100 Blossom Street, Boston, MA, 02114, USA.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Skolny</LastName><ForeName>Melissa N</ForeName><Initials>MN</Initials><AffiliationInfo><Affiliation>Department of Radiation Oncology, Massachusetts General Hospital, Harvard Medical School, 100 Blossom Street, Boston, MA, 02114, USA.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Swaroop</LastName><ForeName>Meyha N</ForeName><Initials>MN</Initials><AffiliationInfo><Affiliation>Department of Radiation Oncology, Massachusetts General Hospital, Harvard Medical School, 100 Blossom Street, Boston, MA, 02114, USA.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Rawal</LastName><ForeName>Bhupendra</ForeName><Initials>B</Initials><AffiliationInfo><Affiliation>Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, 450 Brookline Avenue, Boston, MA, 02115, USA.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Catalano</LastName><ForeName>Paul J</ForeName><Initials>PJ</Initials><AffiliationInfo><Affiliation>Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, 450 Brookline Avenue, Boston, MA, 02115, USA.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Brunelle</LastName><ForeName>Cheryl L</ForeName><Initials>CL</Initials><AffiliationInfo><Affiliation>Department of Physical and Occupational Therapy, Massachusetts General Hospital, Harvard Medical School, 100 Blossom Street, Boston, MA, 02114, USA.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Miller</LastName><ForeName>Cynthia L</ForeName><Initials>CL</Initials><AffiliationInfo><Affiliation>Department of Radiation Oncology, Massachusetts General Hospital, Harvard Medical School, 100 Blossom Street, Boston, MA, 02114, USA.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Taghian</LastName><ForeName>Alphonse G</ForeName><Initials>AG</Initials><AffiliationInfo><Affiliation>Department of Radiation Oncology, Massachusetts General Hospital, Harvard Medical School, 100 Blossom Street, Boston, MA, 02114, USA. ataghian@partners.org.</Affiliation></AffiliationInfo></Author></AuthorList><Language>eng</Language><PublicationTypeList><PublicationType UI="D016428">Journal Article</PublicationType></PublicationTypeList><ArticleDate DateType="Electronic"><Year>2016</Year><Month>05</Month><Day>06</Day></ArticleDate></Article><MedlineJournalInfo><Country>Netherlands</Country><MedlineTA>Breast Cancer Res Treat</MedlineTA><NlmUniqueID>8111104</NlmUniqueID><ISSNLinking>0167-6806</ISSNLinking></MedlineJournalInfo><CitationSubset>IM</CitationSubset><KeywordList Owner="NOTNLM"><Keyword MajorTopicYN="N">Breast cancer</Keyword><Keyword MajorTopicYN="N">Lymphedema</Keyword><Keyword MajorTopicYN="N">Quantification</Keyword><Keyword MajorTopicYN="N">Standardization</Keyword><Keyword MajorTopicYN="N">Temporal baseline</Keyword><Keyword MajorTopicYN="N">Treatment morbidity</Keyword></KeywordList></MedlineCitation><PubmedData><History><PubMedPubDate PubStatus="received"><Year>2016</Year><Month>04</Month><Day>29</Day></PubMedPubDate><PubMedPubDate PubStatus="accepted"><Year>2016</Year><Month>05</Month><Day>02</Day></PubMedPubDate><PubMedPubDate PubStatus="entrez"><Year>2016</Year><Month>5</Month><Day>8</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="pubmed"><Year>2016</Year><Month>5</Month><Day>8</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="medline"><Year>2016</Year><Month>5</Month><Day>8</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate></History><PublicationStatus>ppublish</PublicationStatus><ArticleIdList><ArticleId IdType="pubmed">27154787</ArticleId><ArticleId IdType="doi">10.1007/s10549-016-3821-0</ArticleId><ArticleId IdType="pii">10.1007/s10549-016-3821-0</ArticleId></ArticleIdList></PubmedData></pubmed></record>Pour manipuler ce document sous Unix (Dilib)
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