The aim of this study was to assess the obstetrical and neonatal outcomes of pregnancies in cancer patients and survivors. A retrospective analysis of 68 pregnancies with a history of cancer and 31 newly diagnosed pregnant cancer patients were included in the study. The mean birth weight and the mean gestational age at delivery were significantly lower in the pregnant cancer patients (p < .001). The incidences of delivery less than 34 weeks were 8.8% and 29.1% in the cancer survivors and cancer diagnosed during pregnancy groups respectively (p < .01). In 23 (76.4%) pregnant cancer patients, a single or a combination of treatment modalities was initiated. There were four (12.9%) maternal deaths in pregnant cancer patients. There were no early neonatal death and any congenital anomaly detected in the newborns. Pregnancy in cancer patients and cancer survivors has completely different clinical outcome. Pregnancy in cancer patients has increased the risk of pregnancy complication.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1080/01443615.2017.1318265 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Role of P2X7 receptor in the progression and clinicopathological characteristics of gastric cancer.
Sci Rep
December 2024
Department of Gastroenterology, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang city, Jiangxi province, China.
P2X7 receptor (P2X7R) plays a role in regulating tumor progression, but it is unclear whether P2X7R affects the pathological characteristics of patients with gastric cancer and the activity of gastric cancer cells. Therefore, this study preliminarily investigated the relationship between P2X7R and clinicopathological features of patients with gastric cancer, and further explored the effect of P2X7R on the proliferation, migration and invasion of gastric cancer cells through functional experiments. The results showed that P2X7R was highly expressed in gastric cancer tissues and gastric cancer cells.
View Article and Find Full Text PDFImpact of body composition and muscle health phenotypes on survival outcomes in colorectal cancer: a multicenter cohort.
Sci Rep
December 2024
Postgraduate Program in Health Sciences, Health Sciences Center, Federal University of Rio Grande do Norte, Natal, RN, Brazil.
Body composition abnormalities are prognostic markers in several types of cancer, including colorectal cancer (CRC). Using our data distribution on body composition assessments and classifications could improve clinical evaluations and support population-specific opportune interventions. This study aimed to evaluate the distribution of body composition from computed tomography and assess the associations with overall survival among patients with CRC.
View Article and Find Full Text PDFSerum and plasma as a good candidates of body fluids for detection lung cancer by FTIR liquid biopsy.
Sci Rep
December 2024
Department of Biochemistry and Molecular Biology, Medical University of Lublin, 20-093, Lublin, Poland.
Using Fourier Transform Infrared spectroscopy (FTIR), it is possible to show chemical composition of materials and / or profile chemical changes occurring in tissues, cells, and body fluids during onset and progression of diseases. For diagnostic application, the use of blood would be the most appropriate in biospectroscopy studies since, (i) it is easily accessible and, (ii) enables frequent analyses of biochemical changes occurring in pathological states. At present, different studies have investigated potential of serum, plasma and sputum being alternative biofluids for lung cancer detection using FTIR.
View Article and Find Full Text PDFAttention-guided convolutional network for bias-mitigated and interpretable oral lesion classification.
Sci Rep
December 2024
Faculty of Dental Medicine and Oral Health Sciences, McGill University, Montreal, Canada.
Accurate diagnosis of oral lesions, early indicators of oral cancer, is a complex clinical challenge. Recent advances in deep learning have demonstrated potential in supporting clinical decisions. This paper introduces a deep learning model for classifying oral lesions, focusing on accuracy, interpretability, and reducing dataset bias.
View Article and Find Full Text PDFBidirectional recurrent neural network approach for predicting cervical cancer recurrence and survival.
Sci Rep
December 2024
School of Engineering and Technology, Sunway University, No. 5, Jalan Universiti, Bandar Sunway, Petaling Jaya, 47500, Selangor Darul Ehsan, Malaysia.
Cervical cancer is a deadly disease in women globally. There is a greater chance of getting rid of cervical cancer in case of earliest diagnosis. But for some patients, there is a chance of recurrence.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!