Information extraction from full text scientific articles : Where are the keywords ? Background To date , many of the methods for information extraction of biological information from scientific articles are restricted to the abstract of the article . However , full text articles in electronic version , which offer larger sources of data , are currently available . Several questions arise as to whether the effort of scanning full text articles is worthy , or whether the information that can be extracted from the different sections of an article can be relevant . Background Most applications of information extraction from the scientific medical bibliography use the Abstract of the publication -LRB- for review see for example -LSB- 1-3 -RSB- -RRB- . In the context of information extraction in molecular biology it is usually understood that the information to be extracted from an article are words regarding biological concepts that could synthesize the main points of the article -LRB- keywords -RRB- . Therefore the Abstract of a paper is a good target for information extraction because by definition an abstract synthesizes the content of the article . Moreover , abstracts are available in public databases . However , nowadays most journals are also available in electronic version , and thus full text articles can be used for information extraction . It is obvious that the full text of an article contains more information than its Abstract . However , in approaching full text analysis several problems must be tackled . On the one hand , the storage of full text articles requires more disk space and the analysis needs more computational capacity . On the other hand , an Abstract , as a summary , contains a high frequency of relevant terms -LRB- keywords -RRB- , but this may not be the case of the rest of the article . Other questions regard the quality of the information carried by different sections of an article . First of all , is the information in full text organized enough so that keywords can be extracted ? Secondly , different biological concepts -LRB- for example , gene and protein names , tissue names , organisms , experimental conditions , etc. -RRB- may be located in different parts of the article . Or it could be that a word has a different meaning depending on the section where it is located -LRB- the word has a context dependent meaning -RRB- . For example , regarding gene names , those found in the Methods section may refer mostly to analytical tools rather than being relevant to the biological phenomenology described in the whole article . In summary , it would be good to quantify and qualify the information in a full text article before embarking in large scale extraction of particular items of information . With this goal in mind , we analyzed in this work the kind of information that is attached to different parts of an article and we tried to quantify how much information can be found in each section of an article . This should help to state some guidelines for researchers attempting to extract particular keywords -LRB- words synthesizing the content of the article -RRB- from full text articles . Results Text Corpus As previously stated , the major objective of this work was to compare the information defined as keyword content carried by different sections of a paper , especially the differences between the Abstract and the rest . Therefore , as source for our analysis we used a set of full text articles with a regular section structure , in our study having a defined Abstract , Introduction , Methods , Results , and Discussion -LRB- A , I , M , R , D -RRB- . Another requirement was certain homogeneity of style across the articles -LRB- for example , a similar length of the Methods section -RRB- and , since there is great interest in the field of data mining on the detection of gene names , the subject should be related to Genetics . Thus , we chose the 104 articles published in Nature Genetics from June 1998 -LRB- volume 19 , issue 2 -RRB- to June 2001 -LRB- volume 28 , issue 2 -RRB- , which comply with the AIMRD structure . Note that other journals , or even the Letters of the very same Nature Genetics , might have a different structure -LRB- for example , lacking separated I , M , R , D sections -RRB- . Selection of Keywords To simplify matters , and following our previous work -LSB- 4 -RSB- , we focused on the extraction of relevant words -LRB- keywords -RRB- regarding objects , detected as nouns from natural text by a standard grammatical tagger -LRB- TreeTagger , Helmut Schmid , IMS , Stuttgart University , -RRB- . In order to derive keywords from the section of an article , we first compute the associations between the words in the section . Here , we take the sentence as the unit of text to look for associations , that is , two words are associated in the context of a section if they co-occur repeatedly in sentences within that section -LRB- see METHODS -RRB- . Since words associated strongly to many other words are relevant to the matter that is dealt in the article -LSB- 5 -RSB- we use a score -LRB- K -RRB- that is higher for words with many and strong relations to other words -LRB- see METHODS -RRB- . This measure is used to select words as keywords , in this case , related to objects such as proteins , genes , organisms , etc. . In order to evaluate the performance of the keyword detection , we observed how the selected keywords matched the MeSH -LRB- Medical Subject Headings , -RRB- terms attached by indexers at the National Library of Medicine to these 104 articles -LRB- 18.6 on average -RRB- . Since MeSH terms can be composed of several words -LRB- for example , `` Learning Disorders '' -RRB- , we selected those composed of a single word -LRB- 6.80 terms on average -RRB- . We noted that the most unspecific -LRB- for example , animal -RRB- were often not present in the text and thus could not be matched by a keyword as opposed to species names -LRB- mouse , mycobacterium , human -RRB- , or anatomical terms -LRB- hippocampus , cerebellum , breast -RRB- . Of those single-word MeSH terms , 4.91 were found on average in the article -LRB- as nouns -RRB- , and 2.22 were among the set of selected keywords -LRB- above K > = 0.3 -RRB- . Obviously , a more accurate comparison to MeSH terms would require the detection of bigrams , and trigrams -LRB- keywords composed of multiple words -RRB- , but this is out the scope of our work . The recall when matching the original MeSH terms -LRB- 6.80 on average -RRB- went down from 4.91 / 6.80 = 0.72 in the dictionary of 470.6 different nouns present in an article to 2.22 / 6.80 = 0.33 in the 66.6 keywords selected . However , since the size of the list of all nouns found in an article -LRB- 470.6 -RRB- is much larger than the number of keywords -LRB- 66.6 -RRB- , the precision in matching the MeSH terms of an article increased from 4.91 / 470.6 = 0.010 to 2.22 / 66.6 = 0.033 . Keyword Selection by Section The number of words selected upon a threshold in the K value varies for different sections -LRB- see Figure 1 -RRB- . The first observation is that there are a small number of words that have much better K scores than the rest . This means that the organization of words makes it possible to extract keywords for all the five considered sections . Figure 1 Average number of keywords versus K for A , I , M , R , and D sections . The average number of nouns per section is , A = 52 , I = 171 , M = 404 , R = 600 , D = 331 . The number of selected words is very similar for all sections for very high values of K -LRB- above 0.8 -RRB- . Above a threshold on K -LRB- K > = 0.5 ; see Table 1 -RRB- the resulting number of keywords is quite similar for Introduction and Methods -LRB- around 15 for each -RRB- with the other three sections producing around nine keywords . However , if one accounts for the size of the sections it is obvious that the frequency of keywords -LRB- selected with K > = 0.5 -RRB- per noun is the best in the Abstract -LRB- 0.18 -RRB- , followed by the Introduction -LRB- 0.08 -RRB- , with Methods , Results , and Discussion lagging behind . This justifies data mining strategies that focus in the analysis of Abstracts in order to minimize computational resources . However , this result already indicates that not all keywords are in the Abstract , and that therefore mining the rest of the article may be worthy . Table 1 Keyword selection per section . all K > = 0.3 K > = 0.4 K > = 0.5 A 52.17 19.44 14.42 9.77 I 171.32 31.03 20.47 14.00 M 404.19 54.24 28.50 15.80 R 599.98 24.74 12.74 7.85 D 331.04 26.16 14.25 8.75 Average number of nouns per section -LRB- all -RRB- , or number of those selected as keywords for three different thresholds on the K score . Sections Display Heterogeneous Information As a way to show that the keyword content in different sections is heterogeneous , we examined which keywords -LRB- if any -RRB- were selected in all the sections of an article . Our results indicate that , as it could be expected , not many keywords are present in every section and those are not very relevant . Even for a low threshold of K > = 0.3 , there is on average only one of such general keywords per article . Those are often non-informative words such as `` gene '' , or `` protein '' . This indicates that the information is unevenly distributed across the sections of the article , that is , different sections contain different kind of information . We illustrate the heterogeneity of the information by section with the keywords selected -LRB- for K > = 0.5 -RRB- for a particular article -LSB- 6 -RSB- -LRB- Figure 2 -RRB- . This work deals with a mutation of the Nf1 gene of mouse -LRB- an exon loss -RRB- that produces learning deficits . The only keyword present in every section is the organism under study , the mouse . If the Methods section is excluded , only one single more keyword -LRB- mutation -RRB- is selected . Other three-section overlaps give more interesting keywords such as the name of the gene under study -LRB- Nf1 , neurofibromin -RRB- , a domain contained in the resulting protein -LRB- GAP -RRB- , the method for testing learning performance of mice -LRB- maze -RRB- , or the resulting phenotype -LRB- impairment , lethality -RRB- . Keywords unique to different sections tend to correspond to the different information contained in each section . For example , the keywords unique to the Methods section deal with reagents and techniques -LRB- antibody , amersham , tris , primer -RRB- . Figure 2 The keywords selected for an article -LSB- 6 -RSB- with a K > = 0.5 are represented as they appear in the different sections of the article . In order to quantify the differences and similarities of content across the article we have used the number of keywords that are shared between different sections -LRB- Table 2 -RRB- . The values indicate that the Methods section is the most different of all . In Methods , the content is usually focused on the techniques and protocols used , and not so much on the biological phenomena that is the main subject of the article . This alone explains why those keywords present in every section -LRB- for example protein , gene -RRB- are scarce and uninteresting . Table 2 Average number of keywords -LRB- K > = 0.5 -RRB- shared by two sections for the corpus of 104 articles . A I M R D A 2.01 0.92 1.77 2.20 I 2.01 0.81 1.34 2.02 M 0.92 0.81 1.55 1.02 R 1.77 1.34 1.55 1.99 D 2.20 2.02 1.02 1.99 Regarding similarities between sections , A , I , and D are evenly similar among them , and R is the closest to M , as it is shown when plotting the distance matrix of Table 2 as a dendogram -LRB- see Figure 3 -RRB- . This is probably due to the fact that the Results section deals with the protocols used , although not as explicitly as the Methods section . The Discussion focuses again on the biological results -LRB- stressing their relation to the current knowledge -RRB- without detailing the techniques that have already been explained in Methods and justified in Results . Figure 3 In order to display graphically the similarity between sections regarding keyword content , we took the inverse of the average number of shared keywords -LRB- Table 2 -RRB- as a measure of dissimilarity between sections , and we plotted it as a dendogram -LRB- using -LSB- 19 -RSB- -RRB- . This result indicates that each section contains certain keywords that are unique to the section . In the following we try to characterize what are the differences in content between sections . Qualitative Analysis of Subjects per Section To make a deeper analysis of the kind of information present in each of the sections , we classified in seven categories a set of words present in our corpus of 104 articles -LRB- among the most frequent nouns -RRB- . In order to do so as unambiguously as possible , we selected words that matched MeSH descriptors also consisting on that single word and belonging to only one major MeSH category -LRB- see METHODS -RRB- . We added another category not present in MeSH , that of `` Units , Dimensions , & Parts '' in order to account for many terms that are currently not MeSH terms but are of interest to us . The results -LRB- See Figure 4a -RRB- indicate that the large sections are a good source of keywords , obviously Methods gathering many terms related to techniques . Introduction , Results and Discussion contain a good deal of information regarding diseases . However , again , the Abstract section is shown as the best source for most subjects regarding frequency of keywords -LRB- Figure 4b -RRB- except for those typical of the Methods section -LRB- Techniques & Equipment ; Chemicals & Drugs -RRB- . Figure 4 Word categories present in the five sections under analysis . Classes according to MeSH are A -LRB- Anatomy -RRB- , B -LRB- Organisms -RRB- , C -LRB- Diseases -RRB- , D -LRB- Chemicals & Drugs -RRB- , E -LRB- Techniques & Equipment -RRB- , G -LRB- Biological Sciences -RRB- . An additional class X was defined in this work -LRB- Units , Dimensions , & Parts -RRB- . The number of words used for the analysis was 36 -LRB- class A -RRB- , 14 -LRB- B -RRB- , 11 -LRB- C -RRB- , 47 -LRB- D -RRB- , 33 -LRB- E -RRB- , 41 -LRB- G -RRB- , 49 -LRB- X -RRB- . -LRB- a -RRB- Average number of occurrence of words of each subset per section . -LRB- b -RRB- Frequency of words of each subset per total number of words for each section . Distribution of Gene Names Since the detection of gene and protein names is a very important subject , broadly used for the detection of macromolecular interactions -LRB- see for example -LSB- 7 -RSB- -RRB- , and because , as stated in the introduction , we are concerned about the relevance of matching gene names in different sections of an article , we examined the distribution of gene names across sections . From a long list of genes names derived from the SWISSPROT database -LSB- 8 -RSB- , we selected a very restricted set of 539 genes whose names are composed of three letters followed by one single digit , thus very difficult to be mistaken to other words not being genes . For example , there are gene names called Not or That . Shorter names -LRB- e.g. A6 -RRB- can also be a problem . A total of 224 gene names out of the 539 was matched in 76 of the 104 articles . The Results section was the one with the greatest number of unique gene names -LRB- Figure 5a -RRB- . Again , the Abstract , and then the Introduction , are the sections with the highest frequency of these names -LRB- Figure 5b -RRB- . Figure 5 Distribution of matches to a set of 224 gene names across sections . -LRB- a -RRB- Average number of unique gene names per section . -LRB- b -RRB- Frequency of different gene names per total of nouns for each section . In order to illustrate the problems that affect gene-name identification if context is ignored -LRB- even using gene names apparently easy to recognize -RRB- -LRB- discussed for example in -LSB- 9 -RSB- -RRB- we checked manually the context of gene names that were exclusively mentioned in the Methods section . Of the 224 genes , just 24 were mentioned in the Methods section of the corresponding 14 articles and not elsewhere -LRB- see Table 3 -RRB- . In five of the 14 articles , the name was referring to a non-gene object -LRB- three restriction endonucleases , a vector name , and a fibroblast cell strain -RRB- . In five articles , the gene was mentioned in a technical context -LRB- usually , the gene mRNA level was used for analysis of cell state -RRB- and no biological process involving the gene was described . In only five articles we found the mention of the gene name relevant -LRB- See Table 3 -RRB- . Additionally , we noted that of these 24 gene names , at least two -LRB- Pbp2 , Pom1 -RRB- could refer to two non-homologous -LRB- unrelated -RRB- genes , and another one -LRB- Sac1 -RRB- to four ; such polysemous gene names complicate gene identification from text . Biologists are aware of such problems -LRB- see for example -LSB- 10 -RSB- -RRB- . In summary , extreme caution should be applied with gene names appearing uniquely in the Methods section because the context of gene names there is very different to that seen in the rest of the article . If automated methods to extract gene names from text are applied to the Methods section , those that explore the context of gene names using part-of-speech tagging -LRB- for example , -LSB- 11 -RSB- -RRB- or Hidden Markov Models -LRB- for example , -LSB- 7 -RSB- -RRB- should then perform better than those that just take co-occurrences of gene names -LSB- 12,13 -RSB- . Table 3 Detection of gene names appearing only in the Methods section . Ref Restriction endonucleases Msp1 v27.n3 .277 Incorrect : Pst1 v19.n4 .340 Sac1 v27.n4 .375 Vector name Psg5 v23.n3 .287 Cell strain Tig3 v26.n3 .291 Definition of a Yeast strain Can1 , Leu2 , Lys2 , Trp1 v26.n4 .415 In array Faf1 v20.n3 .266 Correct -LRB- technical context -RRB- : Growth detection Mcm5 , Mcm6 v25.n3 .263 Platelet mRNA analysis Pbp2 v23.n2 .166 Primers used to determine embryo sex Zfy1 , Zfy2 v27.n1 .31 Analysis of mutant phenotypes Pmd1 v24.n4 .355 cDNA probe Rab2 v19.n2 .134 Correct : SNP found in cDNA Add3 , Npr2 v22.n3 .239 Identifier given Pom1 v28.n3 .223 Detection of meiosis specific genes Mei4 , Mek1 , Sps4 , Zip1 v26.n4 .415 Ref : reference of the article in Nature Genetics by volume , issue number and first page of the article . Discussion There is a clear need for doing information extraction of biological data from full text scientific articles and the means for doing it are there with computers better suited for faster computation every day and new methodologies for Natural Language Processing that can be used for biomedical literature -LRB- see for example -LSB- 14 -RSB- -RRB- . Regarding the source of data , the full text electronic versions of journals are now more the rule than the exception , with initiatives in the way towards the construction of large public repositories of such information -LRB- although hotly debated ; see about PubMed Central -LSB- 15,16 -RSB- -RRB- . In this work we have shown that the distribution of information -LRB- as keywords -RRB- in full text articles is heterogeneous and that there is certain correspondence of article sections with different kind and density of relevant data . The Abstracts are shown as the best repository from the point of view of having many keywords in a short space , justifying previous information extraction approaches . The lack of large repositories of full text articles in contrast to the current eleven million of references -LRB- many of them with their abstract -RRB- in the MEDLINE database , are another advantage of the Abstract approach . However , we have shown that there is much more relevant information -LRB- at least in a ratio of 1:4 regarding gene names , anatomical terms , organism names , etc. -RRB- in the rest of the article . We have demonstrated that the information is structured enough to get important numbers of relevant keywords , but that for certain words -LRB- such as gene names -RRB- caution has to be taken regarding the context of the word . We propose that the text mining of full text articles should be approached with different strategies for different sections . Beyond the Abstract , the Introduction looks like the best place to look for protein and gene names -LRB- and interactions -RRB- since it is probably describing current knowledge . The Discussion section , that interprets the results and put them in context with the current knowledge , looks like the third best place for mining such information , with Methods probably as the worst place . The Results section could be problematic given its mixed nature between Methods and the rest . Regarding other subjects , such as keywords about biological concepts -LRB- species , tissues , diseases , etc. -RRB- , again the Abstract and then the Introduction section look like the best sections to mine regarding frequency of such keywords , but Results and especially Discussion seem better from a quantitative point of view . The Methods section is clearly appropriated for looking for technical data , measurements , and chemicals . Respect to chemicals , again , their context can be completely different in this section compared to the rest . Conclusions Extraction of biological information from full text looks promising , but context must be regarded . Part of this context is given by the situation of the text under analysis within the article . Therefore , tuning the extraction of information to the section is probably a good strategy , and for particular tasks some sections should be avoided . We have shown that the kind of simplistic annotation that constitutes tagging a fragment of an article as belonging to a characteristic section is already useful for text mining . But further tagging using markup codes in XML style -LSB- 17 -RSB- identifying biological objects and concepts -LRB- under development ; see for example -LSB- 18 -RSB- or the GENIA project -RRB- could ultimately make text mining a children 's game . We hope for future interfaces for writers of Molecular Biology articles that should do the job upon validation by the authors -LRB- for example , marking every occurrence of a gene name with a unique and stable link to any of the existing gene sequence databases -RRB- . For this to happen , the collaboration between both scientists and publishers will be very important . Methods Derivation of Associations between the words of a section Given a section from an article , we split the text in sentences using a standard part of speech tagger -LRB- TreeTagger -RRB- . We only computed associations between the words identified from the tagging as nouns . Following -LSB- 4 -RSB- , the association between two words -LRB- wi , wj -RRB- -LRB- for example , `` cell '' and `` cycle '' -RRB- can be modeled as the degree of inclusion of one word into the other -LRB- -RRB- which can defined as the fuzzy binary relation given by : , that is , the ratio of the number sentences where both words wi and wj co-occur to the number of sentences the word wi occurs . This is an asymmetric relation very appropriate to model hierarchical relations between words as they happen in natural text . For example , in some Cell Biology context , the word `` cycle '' could appear always related to the word `` cell '' -LRB- as in `` cell cycle '' -RRB- , but the word `` cell '' can be related to many other words such as in `` cell growth '' , `` cell membrane '' , or `` cell nucleus '' . Accordingly , the inclusion value of the word `` cycle '' into `` cell '' will be close to one and the inclusion value of the word `` cell '' into the word `` cycle '' will be close to zero . Selection of Keywords We identify a word as relevant for the text analyzed if it establishes many and strong relations to other words -LRB- following -LSB- 4 -RSB- -RRB- . Therefore , in a given section , we define a score for a word wi that is equal to , normalized to the maximum value found for K of any word in that section . Then , the keywords of the section are defined as those words that have a K score above a certain value . Classification of Words in Subjects In order to classify words into categories we used the following procedure . We chose the MeSH -LRB- Medical Subjects Headings -RRB- classification from the National Library of Medicine . All MeSH terms -LRB- including official synonyms -RRB- composed of one single word were selected and then the stem of the word was computed using TreeTagger . The words present in our corpus of 104 articles were ordered by frequency and all words occurring more than 200 times were selected . Those matching the selected single-word MeSH headers from six categories -LRB- A , B , C , D , E , and G ; See the caption of Figure 4 for descriptions -RRB- were selected as belonging to those classes . In order to avoid possible miss-annotations , words matching more than one category were discarded . Manual analysis of the resulting table of associations was carried out in order to check the associations and to make new ones . A new class not present in MeSH -LRB- the X class of `` Units , Dimensions , & Parts '' -RRB- was generated in order to include a large number of terms mainly present in the Methods section . Authors ' Contributions PS carried out the analysis of the keyword distribution from a database of full text articles . CP developed and applied the method to compute keywords . MA prepared the figures -LRB- except fig 2 by PS -RRB- and conceptualised the structure of the paper . PB and MA co-directed the project and contributed to the final manuscript . All authors collaborated during the whole length of the project . All authors read and approved the final manuscript .

B I O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O 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O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O 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Preoperative Chemoradiotherapy with Capecitabine and Oxaliplatin in Locally Advanced Rectal Cancer . A Phase I -- II Multicenter Study of the Dutch Colorectal Cancer Group Background We studied the maximum tolerated dose -LRB- MTD -RRB- and efficacy of oxaliplatin added to capecitabine and radiotherapy -LRB- Capox-RT -RRB- as neoadjuvant therapy for rectal cancer . Colorectal cancer is a major public health problem in the Western world and ranks as the third leading cause of death in both males and females . In 2000 , more than 9000 new colorectal cancer patients were registered in the Netherlands , of whom 25 % had rectal cancer .1 Surgical resection is the only curative treatment . However , following potentially curative resection , local recurrence rate varies between 5 and 40 % .2 -- 4 Total mesorectal excision -LRB- TME -RRB- is now the standard technique for primary resectable rectal cancer and has significantly improved local control .4 -- 6 The cornerstone of the TME technique is the complete removal of the rectum and mesorectum to realize free circumferential resection margins . Adam showed in 1994 that the incidence of local recurrence 5 years after resection will rise from 10 -- 78 % in case of circumferential margin -LRB- CRM -RRB- involvement .7 So downstaging before the TME procedure may decrease the incidence of CRM involvement and local recurrence . In the Dutch TME trial , no tumor downstaging was detected in the week after 5 × 5 Gy .8 A recent Polish trial demonstrated that a radiotherapy schedule of 50.4 Gy combined with chemotherapy -LRB- 5-FU/Leucovorin -RRB- followed after 4 -- 6 weeks by surgery resulted in a significant higher percentage of downstaging compared with short-term preoperative radiotherapy of 5 × 5 Gy followed by surgery within 7 days .9 So downstaging is dependent on both the total radiotherapy dose and the interval between the end of the radiotherapy and the surgery . In general , to achieve downstaging this interval needs to be at least 6 weeks and the dose needs to be at least 45 Gy .9 Although the obtained downstaging after neoadjuvant radiochemotherapy did result in a favorable prognosis ,10 it was not clear until recently whether the addition of chemotherapy to preoperative radiotherapy could increase the amount of downstaging and thus improve local control . The evidence that the addition of chemotherapy to preoperative radiotherapy improves local control rates has recently been shown by two separate trials . The EORTC 22921 trial has a two by two factorial design and randomized between preoperative radiotherapy -LRB- 45 Gy -RRB- versus preoperative chemoradiotherapy -LRB- 45 Gy combined with 5-FU/Leucovorin -RRB- . The results demonstrated an increased local control rate for the chemoradiation arm : 91 % versus 83 % .11,12 A similar result was found in the French FFCD 9203 study , which randomized between preoperative radiotherapy -LRB- 45 Gy -RRB- and preoperative chemoradiotherapy -LRB- 45 Gy and 5-FU/Leucovorin -RRB- and which showed local recurrence rates of 16.5 % and 8 % , respectively .13 Based on these studies , prolonged preoperative chemoradiation is considered the standard treatment for resectable locally advanced rectal cancers . The EORTC study and the French study employed 5FU bolus injection modulated with leucovorin . However 5FU administered by continuous infusion or orally -LRB- capecitabine / UFT -RRB- may be more effective and less toxic than 5FU administered by bolus injection .14 -- 16 In parallel , the results of palliative chemotherapy in advanced colorectal cancer have been substantially improved by the combination of 5FU with oxaliplatin or irinotecan -LRB- reviewed by Punt17 -RRB- . Both in vivo and in vitro , oxaliplatin has been shown to have at least an additive interaction with radiotherapy in the management of digestive tract tumors .18 -- 20 Incorporation of those drugs in combined treatment strategies could substantially improve the results obtained with bolus 5FU alone in downstaging and R0 resection rates in patients with locally advanced rectal cancer . We investigated the combination of capecitabine and oxaliplatin given concomitantly with radiotherapy in patients with locally advanced rectal cancer . The optimal dose of oxaliplatin was first established in a phase I study , and in the following phase II study the efficacy of this regimen was tested . PATIENTS AND METHODS Objectives The objective of the phase I study was to determine the maximum tolerated dose -LRB- MTD -RRB- of oxaliplatin in combination with a fixed dose of capecitabine and radiotherapy , and the objective of the phase II study was to determine the R0 resection rate and pathological complete response rate -LRB- pCR -RRB- . Eligibility Criteria Eligibility criteria included histologically documented adenocarcinoma of the rectum within 15 cm from the anal sphincter , locally advanced stage T3 -LRB- distance to the endopelvic fascia < 2 mm -RRB- or T4 tumors based on computed tomography -LRB- CT -RRB- or magnetic resonance imaging -LRB- MRI -RRB- findings , performance status -LRB- Eastern Cooperative Oncology Group -RRB- 0 -- 2 , age > 18 years old , adequate hematological , liver function , and other laboratory parameters -LRB- white blood cells 3.0 × 109/L , platelets > 100 × 109/L , creatinin clearance > 50 mL/min , bilirubin < 1.5 times the upper limit of the normal range -LRB- ULN -RRB- , and written informed consent . Patients with reproductive potential should use adequate contraceptive measures . Patients were excluded in case of prior chemotherapy and/or pelvic radiotherapy , acute bowel obstruction without colostomy , uncontrolled ischemic heart disease , peripheral neuropathy , or any uncontrolled serious systemic disease . The protocol was approved by the local ethics committees of all four participating hospitals . The study was performed within the framework of the Dutch Colorectal Cancer Group -LRB- DCCG -RRB- . TREATMENT Radiotherapy All patients received radiation delivered by an isocentric three - or four-field technique , using a linear accelerator of at least 10 MV . The patients were treated in either supine or prone position with a full bladder . The radiation field extended superiorly to the L5/S1 junction and covered inferiorly the obturator foramina . The minimal inferior border extended 4 -- 5 cm below the tumor . In case the tumor was located in the lower third of the rectum , the perineum was encompassed in the treatment field . The width of the AP-PA portals had to cover the lateral pelvic inlet with a margin of 1.5 cm . The entire sacrum was included with a dorsal margin of 1.5 cm . Anteriorly , the lateral fields had to encompass the tumor as determined by barium enema -LRB- optional -RRB- and pelvic CT scan . If there was clinical evidence of involvement of the bladder , the prostate , the cervix or the uterine body , not only the internal iliac nodes but also the external iliac nodes were included in the radiation field . Computerized dosimetry was routinely performed . Irradiation was delivered 5 days per week at a dose of 1.8 Gy/day to a total dose of 45 Gy with a boost to the tumor in 3 fractions of 1.8 Gy to a total of 50.4 Gy . Chemotherapy Capecitabine was administered orally twice daily at 1000 mg / m2 on days 1 -- 14 and 25 -- 38 . Oxaliplatin was given twice by intravenous infusion over 2 h , on the first day of radiotherapy and on day 29 . Oxaliplatin doses were planned at 85 , 100 , and 135 mg/m2 . Each dose level was to be administered to at least three patients . If a dose-limiting toxicity -LRB- DLT -RRB- was observed in ≥ 1 patient , a total of 6 patients had to be treated at that dose level . The maximum-tolerated dose -LRB- MTD -RRB- was defined as the level at which ≤ 2 out of 6 patients experienced DLTs without compromizing radiotherapy and surgery and was the recommended dose in the phase II study . Surgery Surgical resection was performed 6 -- 8 weeks after completion of the chemoradiation therapy . The resection was performed according to the principles of total mesorectal excision as described by Heald2 and Enker .21 These principles include sharp dissection under direct vision following the lipoma-like surface of the mesorectum . Proximal transection of the inferior mesenteric artery was in general performed distal to the collateral between the left colic artery and branches of the sigmoid artery . Anterior dissection in male patients was carried out in front of Denonvilliers ' fascia . If tumor extended into the prostate a total exenteration was performed . In female patients , resection of the posterior vaginal wall was performed if necessary . A distal mesorectal margin of 2 cm was considered adequate if bowel continuity was to be restored . Pathology Pathology evaluation was standardized according to national guideliness . The CRM was assessed according to the method of Quirke et al. ,7 and a margin of < 1 mm from the primary tumor to the endopelvic fascia is considered positive . Statistics Twenty patients were to be included at the MTD to detect with a power of 80 % a R0 resectability rate of > 80 % -LRB- with a 95 % CI of 56 -- 94 % -RRB- . Monitoring and Management During Treatment Physical examination and evaluation of toxicity was performed weekly . Complete blood count , electrolytes , creatinine , and total protein were determined weekly . Standard antiemetic prophylaxis with 5HT3 antagonist prior to oxaliplatin infusion was used . Adverse events were classified according to the National Cancer Institute -LRB- NCI -RRB- Common Toxicity Criteria -LRB- CTC -RRB- Version 2.0 . Global quality of life -LRB- QOL -RRB- assessment was evaluated weekly during the chemoradiotherapy using a visual analogue scale -LRB- VASQOL -RRB- in which in a single 10 cm line anchored on the left with `` worst '' and on the right with `` best '' for QOL .22 Dose-limiting toxicities were defined as white blood cell -LRB- WBC -RRB- and platelets < 3.0 and < 100 × 109/L , respectively , before start of the next treatment cycle with oxaliplatin after a maximum delay of one week ; diarrhea grade > 2 ; oral mucositis grade > 1 ; skin toxicity grade > 2 before start of next treatment cycle with capecitabine , despite a delay of dosing for 1 week ; neurosensory toxicity grade > 2 despite a delay in dosing for 1 week ; occurrence of any grade 4 toxicity ; and any event that would compromise the administration of radiotherapy . RESULTS Patients Characteristics Between June 2003 and December 2004 , 22 patients with T3/T4 rectal cancer from four different centers were enrolled in the study . Patient characteristics are shown in Table 1 . All patients were evaluable for toxicity during chemoradiation . One patient was lost to follow-up after chemoradiation -LRB- surgery was performed abroad -RRB- . Therefore , 21 patients were evaluable for clinical outcome after surgery . Twenty patients -LRB- 91 % -RRB- received the planned dose of chemotherapy . All patients received the planned dose of radiotherapy . The median follow-up was 14 months . TABLE 1 . Patient characteristics -LRB- n = 22 -RRB- CharacteristicsNo.Median age -LRB- years -RRB- 58Range -LRB- years -RRB- 45 -- 70Men/Women12/10Performance status 03 119Distance of tumor to anal verge -LRB- cm -RRB- 0 -- 511 5 -- 107 10 -- 153 Unknown1T status T3a17 T4b5a T3 beyond the fascia recti.b T4 : into pelvic organs -LRB- 1 ureter , 2 vagina , 2 prostate -RRB- Toxicity At the first oxaliplatin dose level of 85 mg/m2 , one patient experienced DLT -LRB- hospitalization for grade 3 nausea and grade 2 diarrhea -RRB- . This dose level was then expanded to six patients , and DLT was observed in another patient -LRB- hospitalization for grade 3 diarrhea -RRB- . Therefore , a dose of 85 mg/m2 oxaliplatin was considered the MTD . In the additional 16 patients , two more patients experienced grade 3 diarrhea . Hand-foot syndrome , myelosuppression , and neurotoxicity were observed only in a minority of patients and were of mild severity . The grade 3/4 toxicity data are shown in Table 2 . TABLE 2 . Toxicity in the study population -LRB- n = 22 -RRB- StudyPhase IPhase IIDose oxaliplatin -LRB- number of patients -RRB- 85 mg/m2 -LRB- 3 -RRB- 85 mg/m2 -LRB- 3 -RRB- -LRB- 22 -RRB- Toxicity grade -LRB- NCI CTCV2 .0 -RRB- Toxicity grade -LRB- NCI CTCV2 .0 -RRB- Toxicity grade -LRB- NCI CTCV2 .0 -RRB- 343434Leukopenia -- -- -- -- -- -- Neutropenia -- -- -- -- -- -- Thrombopenia -- -- -- -- -- -- Anemia -- -- -- -- -- -- Diarrhea -- -- 1 -- 4 -- Abdominal pain -- -- -- -- -- -- Nausea1 -- -- -- -- -- Mucositis -- -- -- -- -- -- Neurotoxicity -- -- -- -- -- -- Surgery TME surgery was performed after a median of 47 days -LRB- range 4 -- 8 weeks range in days -RRB- following the completion of chemoradiation . Mean hospitalization time was 14 days -LRB- range 9 -- 95 ; 70 % < 21 days -RRB- . The main surgical complications were : major bleeding -LRB- 1 -RRB- , rectal perforation -LRB- 1 -RRB- , ureter lesion -LRB- 1 -RRB- . Postsurgery treatment related complications were seen in 12 patients with mild wound infections -LRB- 6 -RRB- , wound dehiscences -LRB- 2 -RRB- , -LRB- sub -RRB- ileus -LRB- 4 -RRB- , rhabdomyolysis -LRB- 1 -RRB- , and in one patient a life-threatening multiorgan failure after a perforation in an abcess located near the anus praeter . Rhabdomyolysis is an unusual complication . In this patient it was probably caused by the operation procedure and not by this specific procedure as there were no other postoperative complications . Three patients -LRB- 15 % -RRB- needed reoperation for perforation -LRB- 1 -RRB- and pelvic abscesses -LRB- 2 -RRB- . The 60-day mortality rate was nil . Efficacy Twenty-one patients with a T3 -- T4 tumor based on CT or MRI underwent surgery with 10 abdominoperineal resections -LRB- APRs -RRB- and 10 low anterior resections -LRB- LARs -RRB- ; in one patient the tumor was not resectable . A R0 resection was achieved in 17 patients -LRB- 81 % , 95 % CI 58 -- 95 % -RRB- . A pCR was observed in 2 patients -LRB- 10 % , 95 % CI 1 -- 30 % -RRB- , and in one patient -LRB- 5 % -RRB- the surgical specimen only showed minimal microscopic disease . The postradiotherapeutic pathologic staging yielded in seven patients -LRB- 33 % ; 95 % CI 15 -- 57 % -RRB- a downstaging to pT0 -- T2 . After a median follow-up of 14 months , four patients have died due to metastatic disease and one patient has experienced a local recurrence . Quality of Life The VASQOL score was measured weekly during chemoradiotherapy . The QOL decreased after 4 weeks treatment from 80 % in week 4 to 60 % in week 6 -LRB- p < .002 , student-t test -RRB- . DISCUSSION Based on the EORTC 22921 and FFCD 9203 phase III studies ,11,13,23 preoperative chemoradiation with 5FU and 45 Gy or higher is now considered to be the standard of care for locally advanced rectal cancer . In these studies , 5FU was given as a daily bolus infusion in week 1 and 5 . To improve on these results , we tested the feasibility and efficacy of the addition of oxaliplatin to capecitabine in this combined treatment strategy . Our recommended dose for the phase II study was oxaliplatin 85 mg/m2 on day 1 and 29 plus capecitabine 1000 mg/m2 twice daily during 14 days starting on day 1 and 25 in combination with radiotherapy at a total dose of 50.4 Gy . In our phase I/II study , we found grade III diarrhea in 19 % , a R0 resection in 81 % , downstaging to T0 -- 2 in 33 % , and a pCR in 10 % of patients . Table 3 summarizes the studies with the addition of oxaliplatin to a fluoropyrimidine -LRB- IV or orally -RRB- and radiotherapy . These studies show a toxicity and efficacy profile comparable to the results from our study . TABLE 3 . Locally advanced rectal cancer , recent neoadjuvant studies with fluoropyrimidines and oxaliplatin in combination with radiotherapyStudyDesign -LRB- phase -RRB- StageNEBRT -LRB- Gy -RRB- CTR0 -LRB- % -RRB- pCR -LRB- % -RRB- Toxicity grade 3 -- 4 -LRB- % -RRB- TotalDiarrheaMyelotoxicPreoperative radiotherapy vs. chemoradiotherapy -LRB- with 5 FU -RRB- EORTC 2292111,23 IIIT3/T4 101145 -- -- 538a17 -- 1 -- 455FU pre -- 1454 -- 34 -- 9 -- FFCD 920313IIIT3/T476245 -- 9043 -- -- 455FU pre911215 -- -- Bujko9IIIT3/T43165 × 5 -- 8713 -- -- 50.45 FU pre961718 -- -- Preoperative CRT with capecitabineKim30IIT3/T4/N +4550.4 Cap 3 -- 31174 -- Dunst31/Glynne - Jones32IIT3/T4/N +9850.4 + 5.4 Cap 1 -- 422410Chau33IIT3 + , low T3 , N27754Cap 1b99244 deathsYerushalmi16IIT3/T4 -LRB- T2 10 % -RRB- 4650.4 5FU vs Cap 2 -- 17443 -- 302Preoperative CRT with 5 FU based chemotherapy and oxaliplatinGambacorta34IIT33050Tomox -- 3013310Gerard26IIT2/T3/T44050 .4 FU + Ox 1 -- 151853Rodel35IIT3 -- 43250.4 Capox 479191680Carraro36IIT3/T42250 .4 FU + Ox 2 -- 14 -- 2714Aschele25I/IIT3/T4 / N +2550.4 FU + Ox 3892824164Glynne-Jones32I / IIUnresectable9445Capox 278281310 -- Machiels24IIT3/T4/N +4045 Capox 18314 -- 30 -- Hospers -LRB- 2006 -RRB- This studyI/IIT3/T42250 .4 Capox8110 -- 18 -- Cap 1 : 825 mg/m22 × daily , 7 daysCapox 1 : Cap 825 2 × daily , Monday -- Friday , oxali 50 weeklyTomox : raltitrexed 3 , oxali 130 , day 1 , 19 , 38Cap 2 : 825 mg/m2 2 × daily , Monday -- FridayCapox 2 : Cap 650 2 × daily , 7 days , oxali 130 per 2 weeksFU + Ox 1 : 5FU 350 daily , Oxali 130 weekly , week 1 and 5Cap 3 : 825 mg/m2 2 × daily ,14 days -LRB- 2 × -RRB- Capox 3 : Cap 825 2 × daily , 7 days , oxali 60 per 2 weeksFU + Ox 2 : 5FU 375/4 days , Oxali 25/4 days , week 1 and 5Capox 4 : Cap 825 2 × daily , 2 × 14 days , oxali 50 , day 1 , 8 , 22 , 29FU + Ox 3 : 5FU 225 daily , Oxali 60 weeklya ≥ Grade 2 toxicity.b 12 weeks neoadjuvant CAPO . Diarrhea generally occurred during the last 2 weeks of chemoradiation , which was accompanied by a significant decrease in QOL . As shown in Table 2 , the addition of oxaliplatin increases the incidence of toxicities when compared with the use of 5FU alone . The observed postsurgical morbidity -LRB- mild wound infections excluded -RRB- , the reoperations and the median hospitalization time in our study were 30 % , 15 % , and 14 days , respectively , and are comparable with other studies .24 -- 26 We found a similar efficacy in pCR and R0 compared to other studies -LRB- Table 3 -RRB- . However , comparing the efficacy of these regimes is hampered by a number of technicalities . These comprise differences in 1 -RRB- staging techniques , 2 -RRB- the determination of distance of the tumor to the endopelvic fascia , 3 -RRB- pathology techniques , and 4 -RRB- the difference in interval between neoadjuvant treatment and surgery . The staging techniques used to define the locally advanced stage of the primary tumor and lymph nodes are clinical examination , CT , MRI , endoultrasound or combinations , the use of ultrasmall particles of iron oxide -LRB- USPIOs -RRB- .27 These different staging techniques may lead to variabilities in pretreatment staging and therefore compromise the quantitation of downstaging . Moreover , the tumor might be still visible on posttreatment imaging , but it may have become nonvital . The distance of the tumor to the endopelvic fascia will influence the local recurrence rate . The determination of a pCR and an R0 resection depends on the sophistication of the pathology techniques used , and the definition of a R0 resection -LRB- distance tumor to resection or to CRM -RRB- is not uniform . In the various clinical protocols , the time interval between chemoradiotherapy and surgery is not standardized , which may influence the degree of downstaging but also the ultimate results of local cure . Therefore , cross-study comparison should be interpreted with caution . The end points used in this study are known to have a different impact on clinical outcome : a pCR is associated with a low local recurrence rate , and prolonged DFS and is not significantly related to the cT and cN categories .28 R0 resection is known to be a highly relevant prognostic factor .29 Comparing our results on pCR and R0 to other oxaliplatin-containing studies , we found similar results ; however , these were also observed using monotherapy with 5FU or capecitabine -LRB- Table 2 -RRB- . Therefore , it is yet unknown whether the increased toxicity of adding oxaliplatin to a fluoropyrimidine in neoadjuvant chemoradiation schedules results in a clinical benefit for patients with rectal cancer . In conclusion , this multicenter study demonstrated a neoadjuvant regimen with Capox-RT with an acceptable acute toxicity profile . Randomized phase III studies with in the standard arm 5FU will be necessary to show the true benefit of this approach . In such prospective studies , the standardization of the staging technique -LRB- i.e. , the distance of the tumor to the endopelvic fascia -RRB- , TME surgery , radiotherapy , and pathology should minimize the influence of these factors on the outcome .

O O O B O B O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O B O B O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O 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O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O B O O O O O O O O O O O O O O O B O O O O O O O O B O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O B O O O O O B O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O

rectal cancer
radiotherapy
oxaliplatin
capecitabine
chemoradiation