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Smoking and Complications After Cancer Surgery: A Systematic Review and Meta-Analysis

Wong C, Mohamad Asfia SKB, Myles PS, Cunningham J, Greenhalgh EM, Dean E, et al.

JAMA Netw Open, 2025 Mar 03;8(3):e250295.
PMID: 40053349 DOI: 10.1001/jamanetworkopen.2025.0295

IMPORTANCE: Surgical cancer treatments may be delayed for patients who smoke over concerns for increased risk of complications. Quantifying risks for people who had recently smoked can inform any trade-offs of delaying surgery.
OBJECTIVE: To investigate the association between smoking status or smoking cessation time and complications after cancer surgery.
DATA SOURCES: Embase, CINAHL, Medline COMPLETE, and Cochrane Library were systematically searched for studies published from January 1, 2000, to August 10, 2023.
STUDY SELECTION: Observational and interventional studies comparing the incidence of complications in patients undergoing cancer surgery who do and do not smoke.
DATA EXTRACTION AND SYNTHESIS: Two reviewers screened results and extracted data according to the Meta-Analyses of Observational Studies in Epidemiology (MOOSE) reporting guidelines. Data were pooled with a random-effects model and adjusted analysis was performed.
MAIN OUTCOMES AND MEASURES: The odds ratio (OR) of postoperative complications (of any type) for people who smoke currently vs in the past (4-week preoperative cutoff), currently smoked vs never smoked, and smoked within shorter (2-week cutoff) and longer (1-year cutoff) time frames.
RESULTS: The meta-analyses across 24 studies with a pooled sample of 39 499 participants indicated that smoking within 4 weeks preoperatively was associated with higher odds of postoperative complications compared with ceasing smoking for at least 4 weeks (OR, 1.31 [95% CI, 1.10-1.55]; n = 14 547 [17 studies]) and having never smoked (OR, 2.83 [95% CI, 2.06-3.88]; n = 9726 [14 studies]). Within the shorter term, there was no statistically significant difference in postoperative complications between people who had smoked within 2 weeks preoperatively and those who had stopped between 2 weeks and 3 months in postoperative complications (OR, 1.19 [95% CI, 0.89-1.59]; n = 5341 [10 studies]), although the odds of complications among people who smoked within a year of surgery were higher compared with those who had quit smoking for at least 1 year (OR, 1.13 [95% CI, 1.00-1.29]; N = 31 238 [13 studies]). The results from adjusted analyses were consistent with the key findings.
CONCLUSIONS AND RELEVANCE: In this systematic review and meta-analysis of smoking cessation and complications after cancer surgery, people with cancer who had stopped smoking for at least 4 weeks before surgery had fewer postoperative complications than those smoking closer to surgery. High quality, intervention-based evidence is needed to identify the optimal cessation period and inform clinicians on the trade-offs of delaying cancer surgery.
The attractive female body weight and female body dissatisfaction in 26 countries across 10 world regions: results of the international body project I

Swami V, Frederick DA, Aavik T, Alcalay L, Allik J, Anderson D, et al.

Pers Soc Psychol Bull, 2010 Mar;36(3):309-25.
PMID: 20179313 DOI: 10.1177/0146167209359702

This study reports results from the first International Body Project (IBP-I), which surveyed 7,434 individuals in 10 major world regions about body weight ideals and body dissatisfaction. Participants completed the female Contour Drawing Figure Rating Scale (CDFRS) and self-reported their exposure to Western and local media. Results indicated there were significant cross-regional differences in the ideal female figure and body dissatisfaction, but effect sizes were small across high-socioeconomic-status (SES) sites. Within cultures, heavier bodies were preferred in low-SES sites compared to high-SES sites in Malaysia and South Africa (ds = 1.94-2.49) but not in Austria. Participant age, body mass index (BMI), and Western media exposure predicted body weight ideals. BMI and Western media exposure predicted body dissatisfaction among women. Our results show that body dissatisfaction and desire for thinness is commonplace in high-SES settings across world regions, highlighting the need for international attention to this problem.
Polygenic risk modeling for prediction of epithelial ovarian cancer risk

Dareng EO, Tyrer JP, Barnes DR, Jones MR, Yang X, Aben KKH, et al.

Eur J Hum Genet, 2022 Jan 14.
PMID: 35027648 DOI: 10.1038/s41431-021-00987-7

Polygenic risk scores (PRS) for epithelial ovarian cancer (EOC) have the potential to improve risk stratification. Joint estimation of Single Nucleotide Polymorphism (SNP) effects in models could improve predictive performance over standard approaches of PRS construction. Here, we implemented computationally efficient, penalized, logistic regression models (lasso, elastic net, stepwise) to individual level genotype data and a Bayesian framework with continuous shrinkage, "select and shrink for summary statistics" (S4), to summary level data for epithelial non-mucinous ovarian cancer risk prediction. We developed the models in a dataset consisting of 23,564 non-mucinous EOC cases and 40,138 controls participating in the Ovarian Cancer Association Consortium (OCAC) and validated the best models in three populations of different ancestries: prospective data from 198,101 women of European ancestries; 7,669 women of East Asian ancestries; 1,072 women of African ancestries, and in 18,915 BRCA1 and 12,337 BRCA2 pathogenic variant carriers of European ancestries. In the external validation data, the model with the strongest association for non-mucinous EOC risk derived from the OCAC model development data was the S4 model (27,240 SNPs) with odds ratios (OR) of 1.38 (95% CI: 1.28-1.48, AUC: 0.588) per unit standard deviation, in women of European ancestries; 1.14 (95% CI: 1.08-1.19, AUC: 0.538) in women of East Asian ancestries; 1.38 (95% CI: 1.21-1.58, AUC: 0.593) in women of African ancestries; hazard ratios of 1.36 (95% CI: 1.29-1.43, AUC: 0.592) in BRCA1 pathogenic variant carriers and 1.49 (95% CI: 1.35-1.64, AUC: 0.624) in BRCA2 pathogenic variant carriers. Incorporation of the S4 PRS in risk prediction models for ovarian cancer may have clinical utility in ovarian cancer prevention programs.
Fulltext Correction: Polygenic risk modeling for prediction of epithelial ovarian cancer risk

Dareng EO, Tyrer JP, Barnes DR, Jones MR, Yang X, Aben KKH, et al.

Eur J Hum Genet, 2022 May;30(5):630-631.
PMID: 35314806 DOI: 10.1038/s41431-022-01085-y