TNM

The eds.tnm component extracts TNM mentions from clinical documents.

Examples

import edsnlp

nlp = edsnlp.blank("eds")
nlp.add_pipe("eds.sentences")
nlp.add_pipe("eds.tnm")

text = "TNM: pTx N1 M1"

doc = nlp(text)
doc.ents
# Out: (pTx N1 M1,)

ent = doc.ents[0]
ent._.tnm.dict()
# {'modifier': 'p',
#  'tumour': None,
#  'tumour_specification': 'x',
#  'node': '1',
#  'node_specification': None,
#  'metastasis': '1',
#  'resection_completeness': None,
#  'version': None,
#  'version_year': None}

Parameters

PARAMETER	DESCRIPTION
`nlp`	The pipeline object TYPE: `Optional[PipelineProtocol]`
`name`	The name of the pipe TYPE: `str` DEFAULT: `'eds.tnm'`
`pattern`	The regex pattern to use for matching ADICAP codes TYPE: `Optional[Union[List[str], str]]` DEFAULT: `(?:\b\|^)(?<=\(?(?P<version>uicc\|accj\|tnm\|UICC\|A...`
`attr`	Attribute to match on, eg `TEXT`, `NORM`, etc. TYPE: `str` DEFAULT: `TEXT`
`label`	Label name to use for the `Span` object and the extension TYPE: `str` DEFAULT: `tnm`
`span_setter`	How to set matches on the doc TYPE: `SpanSetterArg` DEFAULT: `{'ents': True, 'tnm': True}`

Authors and citation

The TNM score is based on the development of S. Priou, B. Rance and E. Kempf (Kempf et al., 2022).

Kempf E., Priou S., Lamé G., Daniel C., Bellamine A., Sommacale D., Belkacemi y., Bey R., Galula G., Taright N., Tannier X., Rance B., Flicoteaux R., Hemery F., Audureau E., Chatellier G. and Tournigand C., 2022. Impact of two waves of Sars-Cov2 outbreak on the number, clinical presentation, care trajectories and survival of patients newly referred for a colorectal cancer: A French multicentric cohort study from a large group of University hospitals. {International Journal of Cancer}. 150, pp.1609-1618. 10.1002/ijc.33928