Bibliographic record
Abstract
FigureExposure to antineoplastic drugs on the job increased the risk of spontaneous abortion in nurses by 94 percent, according to a new study published online ahead of print in the American Journal of Obstetrical Gynecology (doi: 10.1016/j.ajog.2011.12.010). “We felt it was important to publish these results and again to bring up this issue that even though this is a well-known reproductive hazard, that nurses are still reporting exposure at levels that are showing effects on their pregnancies,” the study's lead author, Christina Lawson, PhD, an epidemiologist at the National Institute for Occupational Health and Safety (NIOSH), said in a telephone interview. Previous studies have suggested the same conclusions that the NIOSH and Harvard University research team came to, she said, but this was the first trial adequately powered to look at confounding factors, including age, other work exposures, parity, and hours worked per week. And, the increase miscarriage risk persisted. The team used data collected by the Nurses' Health Study II, which included 7,482 pregnant nurses fitting the research criteria. The group evaluated the association between the rate of spontaneous abortion and reported individual exposure to antineoplastic drugs, as well as sterilizing agents and x-rays. Pregnancies that ended involuntarily before 20 weeks of gestation were considered “spontaneous abortion.” All three exposures increased the rate of spontaneous abortion after adjusting for the factors noted above. Handling antineoplastic drugs increased risk by 94%, sterilizing agents increased risk by 39%, and x-rays increased risk by 22%, although Lawson said this last finding was considered to be only borderline significant. The link between miscarriage and handling antineoplastic drugs is not surprising. These drugs are designed to target rapidly proliferating cancer cells, Lawson explained. “They're designed to find cells that are rapidly growing and multiplying and kill those. If you think of a developing fetus, they behave the same way that a tumor cell would, as far as growing rapidly, and that's why they're particularly dangerous during pregnancy.” This research will add support to guidelines cautioning any health care workers who might be exposed to these drugs to take caution. “It's not just nurses who may be exposed, but also pharmacists and people who may be working in manufacturing of antineoplastic drugs,” she said. NIOSH published a report in 2010, listing precautionary recommendations for health care professionals on safe handling of antineoplastic and other hazardous drugs. But, Lawson said, more needs to be done to raise awareness of these hazards, so that health care workers know what they need to do to protect themselves. “Keeping an open dialogue between employers and employees about reproductive status is important so that women feel comfortable letting their supervisors know as soon as they think they might be pregnant, so they can be aware, and try to do their best to protect themselves during that vulnerable time,” she said. Catherine Coleman, Assistant Director of the Dana-Farber/Harvard Cancer Center Health Communication Core notes that the next generation of the Nurses' Health Study—NHS3—is now recruiting 100,000+ nurses and nursing students with the goal of advancing knowledge about the effects of nurses' work life on their health. Female RNs, LPNs, and nursing students age 20-46 living in the US or Canada are eligible to join. “Participation takes about one hour per year and is entirely online,” she noted in a comment on the Online-First version of this article. “NHS3 also will continue the study's research into the effects of lifestyle on health as well as important new issues like environment, fertility, hormonal preparations, and adolescent diet.” Further information is available at nhs3.org
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".