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25 Year Old Female Conceiving 6 Months After Last Dose of Rituximab: a Case Report

2010· article· en· W2597397210 on OpenAlexaff
Lydia Y Cheung, Caroline Hamm, Michelle Suga, Mohammed Adie

Bibliographic record

VenueBlood · 2010
Typearticle
Languageen
FieldMedicine
TopicCancer Risks and Factors
Canadian institutionsWindsor Regional HospitalWestern University
Fundersnot available
KeywordsRituximabMedicinePregnancyCD20LymphomaFollicular lymphomaFetusInternal medicineBiology

Abstract

fetched live from OpenAlex

Abstract Abstract 4924 For female patients treated with rituximab, a monoclonal anti-CD20 antibody, it is recommended to wait 12 months post-treatment before pregnancy to avoid fetal B cell depletion. We report a case of a 25 year old female with a history of Grade II follicular lymphoma, Stage III who was treated with CHOP/R and maintenance rituximab therapy which was stopped when she expressed intentions for pregnancy. However, she conceives within only 6 months after her last dose of rituximab. This prompts questions of risks to the fetus. Rituximab is a monoclonal anti-CD20 antibody which targets and destroys normal and malignant CD20 positive B cells. As an IgG molecule, rituximab can cross the placenta, and has been documented to cause B cell depletion and immunosuppression in the fetus (McKeever et al, 2003). During treatment, high drug levels are detectable in the umbilical cord blood, and remains in the patient's blood between 3–6 months post-treatment (Pereg et al, 2007). The half life of rituximab varies with tumour burden and ranges from 3 – 19 days. B cell levels start to recover at 6 months post-treatment and are normal by 12 months. Hence, it is recommended by the manufacturer that pregnancies should be separated from rituximab use by a minimum of 12 months. Current literature regarding rituximab's safety in pregnancy is limited to animal studies and 10 case reports. When pregnant macaque cynomolgus females were exposed in 1st trimester, no teratogenic or embryotoxic effects were shown. There was a decrease in B cell levels but these were reversible by 179 days (McKeever et al., 2003). Among case reports, six involved women treated for hematological conditions. Of these cases, one was inadvertently exposed in 1st trimester and the fetus had B cell depletion that recovered to normal levels by 16 days (Kimby, 2004). All other cases were exposed in 2nd trimester of which two had transient B cell depletion that recovered by 4 months. All babies were healthy at birth, had normal antibody titres after their first vaccinations and normal childhood development at follow-up (Friedrich, 2006; Decker 2006). Four case reports involved rituximab use for non-hematological conditions; two cases of 1st trimester and two cases of 3rd trimester exposure. Only one 3rd trimester case reported transient fetal B cell depletion that recovered by 6 months (Klink, 2008). Again, all babies were healthy at birth and at follow-up, including normal antibody titres after vaccinations. From the cases reported, regardless of trimester exposure, the B cell depletion effect was only transient with no documented short-term or long-term effects on the baby's immune function and overall development. In this case, the patient stopped rituximab therapy 6 months prior to conception. There were no complications during pregnancy or delivery. Furthermore, a healthy baby boy was born at 42 weeks gestation with normal apgar scores, length at 75th percentile, and normal weight of 8 lbs 16 oz. Since the baby was clinically stable after delivery, B cell levels were not drawn. At 3 months old, the baby was healthy and had no difficulties with vaccinations to date. This is yet another case to add to the small literature base, and we hope it can help further inform the usage of rituximab during pregnancy. Disclosures: No relevant conflicts of interest to declare.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0040.002
Science and technology studies0.0030.002
Scholarly communication0.0020.002
Open science0.0010.002
Research integrity0.0060.005
Insufficient payload (model declined to judge)0.0040.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.011
GPT teacher head0.272
Teacher spread0.261 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designCase report
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations1
Published2010
Admission routes1
Has abstractyes

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