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Association between pre-diagnosis and post-diagnosis Alternate Mediterranean Diet and ovarian cancer survival: evidence from a prospective cohort study

Journal of Translational Medicine volume 22, Article number: 860 (2024) Cite this article

Abstract

Background

There is currently a lack of comprehensive evidence regarding the correlation between Alternate Mediterranean Diet (AMED) and the survival of patients with ovarian cancer (OC). This prospective cohort study first assessed the association of AMED, not only pre-diagnosis and post-diagnosis but also the change from pre-diagnosis to post-diagnosis with OC survival.

Methods

A total of 560 OC patients were included in the study, and their dietary intake was assessed using a reliable 111-item food frequency questionnaire. The overall survival (OS) of the patients was monitored through active follow-up and review of medical records until February 16th, 2023. Cox proportional hazard regression models were utilized to compute the hazard ratios (HRs) and their corresponding 95% confidence intervals (CIs).

Results

Out of the total 560 patients with OC, 211 (37.68%) succumbed during a median follow-up period of 44.40 months (interquartile range: 26.97–61.37). Comparative analysis indicated a significant association between the highest tertiles of pre-diagnosis (HR = 0.59; 95% CI 0.38–0.90; Ptrend < 0.05) and post-diagnosis (HR = 0.61; 95% CI 0.41–0.91; Ptrend < 0.05) AMED intake and improved OS as opposed to the lowest tertile. Additionally, a significant linear trend was observed for AMED and OC survival. Notably, decreased intake (more than 5% change) and significantly increased intake (more than 15% change) of AMED from pre-diagnosis to post-diagnosis were linked to worse and better OS, respectively, when compared to the stable intake group (change within 5%). Furthermore, patients displaying consistently higher AMED intake both before and after diagnosis experienced enhanced OS in comparison to those with consistently low AMED intake (HRHigh-High vs. Low-Low = 0.47; 95% CI 0.31–0.70).

Conclusion

High pre-diagnosis and post-diagnosis AMED was associated with an improved OS in patients with OC, suggesting that maintaining a consistently high intake of AMED could potentially benefit the prognosis of OC.

Introduction

Ovarian cancer (OC) ranks as the second leading cause of mortality among gynecologic malignancies on a global scale. In 2022, 324,398 new cases of OC were diagnosed and 206,839 new deaths were reported globally [1]. Given the insignificant and non-specific early symptoms, most patients with OC are already in advanced stages when they are diagnosed and have a short survival time [2]. Although surgery, chemotherapy, and some innovative treatments have been used to treat OC [3], the prognosis remains less than ideal. Thus, there is a pressing need to identify modifiable factors [4], such as diet [5], that may be implemente d to improve survival following an OC diagnosis.

In recent years, with the development of nutritional epidemiology, the relationship between dietary patterns and cancer risk and prognosis has received extensive attention [6]. Among them, the Mediterranean Diet (MED) is a widely recognized healthy eating pattern, and its role in preventing chronic diseases and cancers has been confirmed in several studies [7]. However, considering the differences in dietary patterns in different regions and cultural contexts, researchers have begun to explore alternative models of the MED, the Alternate Mediterranean Diet (AMED), to better adapt to the dietary characteristics of different populations. The AMED retains the core elements of the MED, such as increasing the intake of healthy foods like olive oil, whole grains, vegetables, fruits, nuts, and legumes, while incorporating local ingredients and eating habits to make it more regional and culturally adaptable [8]. Of note, the AMED has garnered significant attention due to its myriads of health benefits, spanning from cardiovascular diseases and neurodegenerative disorders to cancer prevention and mortality reduction [9,10,11].

The growing body of scientific evidence indicates that the AMED could potentially play a crucial role in enhancing cancer prognosis, including OC, owing to its comprehensive and well-balanced nutritional composition [12]. The majority of prior studies have primarily investigated the association between AMED and the occurrence of OC [13]. However, research focusing on the prognosis of AMED in relation to OC is limited. To date, only one prospective cohort study, published in 2024, has examined the correlation between AMED and OC survival. The study revealed that better AMED was associated with lower all-cause mortality [12]. Nevertheless, no prior studies have investigated changes in AMED intake before and after the diagnosis of OC. Therefore, we carried out the present study to assess the association of AMED diet, not only pre-diagnosis and post-diagnosis but also the change from pre-diagnosis to post-diagnosis with OC survival based on a prospective cohort of patients with OC in China, the Ovarian Cancer Follow-Up Study (OOPS). We hope that this study will lead to a further comprehensive understanding of the role of AMED in the improvement of OC outcomes, and provide a scientific basis for the development of personalized dietary interventions.

Materials and methods

Study population

The OOPS is a prospective longitudinal cohort study and aims to collect demographic, clinical, and lifestyle data from patients with OC to assess their associations with cancer-related outcomes [14]. By August 2022, the OOPS recruited 1,082 patients with OC aged 18–79 years via the Shengjing Hospital of China Medical University. Of these, 958 (88.5%) patients consented to participate, 936 (86.5%) patients returned the completed study questionnaire, and 602 (56%) patients provided complete information on pre-diagnosis and post-diagnosis. After excluding implausible energy intake (< 500 or > 3500 kcal/day) (n = 18), leaving out 11 (10%) or more food items (n = 13), incomplete clinical information (n = 11), a total of 560 (51.8%) patients with OC were eligible for this analysis [15] (Fig. 1). The study was approved by the Institutional Review Board of the Ethics Committee of Shengjing Hospital of China Medical University, and all patients signed informed consent before participation.

Fig. 1
figure 1

The flow of participants in the Ovarian Cancer Follow-up Study (OOPS)

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Data collection

In summary, data on pre-diagnosis were collected through a questionnaire administered at the time of diagnosis, and post-diagnosis data were gathered via another questionnaire 12 months following diagnosis [16]. We obtained information on demographics and lifestyle factors, such as dietary intake, physical activity, smoking status, alcohol consumption, tea drinking, education level, income, parity, and menopausal status, through self-administered questionnaires both at diagnosis and 12 months subsequently. The anthropometric measurements, including height and weight, were collected by trained staff using standardized techniques and equipments. Body mass index (BMI) was calculated as weight in kilograms divided by height in squared meters. In addition, clinical characteristics were abstracted using the Shengjing Hospital information system’s electronic medical records. These characteristics included age at diagnosis (continuous, years), histological type (serous or non-serous), International Federation of Gynecology and Obstetrics (FIGO) stage (I-II or III-IV), residual lesions (no, < 1, or ≥ 1 cm), and comorbidities (hypertension, coronary heart disease, diabetes, etc.) (yes or no) [17].

Dietary exposure assessment

Diet information was collected at recruitment using a 111-item food frequency questionnaire (FFQ), which has been verified to have reasonable reliability and validity [18]. Most food groups had repeatability coefficients above 0.5, and most food groups between the FFQ and weighted diet records had Spearman correlation coefficients between 0.3 and 0.7. In this study, participants were asked to retrospectively estimate, on average, the year before and after OC diagnosis, how often they consumed each food listed as well as the frequencies of cooking methods for meat and vegetables. Intake frequency was divided into 7 categories (“almost never”, “2–3 times per month”, “1 time per week”, “2–3 times per week”, “4–6 times per week”, “1 time per day”, and “ ≥ 2 times per day”). Each individual's food intakes (grams/day) were calculated based on consumption frequencies and standard portion sizes. In addition, the average daily nutrient intake was calculated by multiplying the consumption frequency of each food item by the nutrient content of the specified portions, followed by summing the nutrient content across all food items consumed by a participant. The nutrient contents were determined based on the Chinese Food Composition Table [19].

Assessment of Alternate Mediterranean Diet score

The AMED score was adapted from the Mediterranean diet scale by Trichopoulou et al. [20]. Our components include vegetables (excluding potatoes), fruits, nuts, whole grains, legumes, fish, the ratio of monounsaturated to saturated fat, red and processed meats, and alcohol [21, 22]. Participants with intake above the median intake received 1 point for these categories except red and processed meat and alcohol; otherwise, they received 0 points (Supplementary Table S1). For the red and processed meat consumption below the median received 1 point. We assigned 1 point for alcohol intake between 5 and 15 g/d, which represents approximately one 12-oz can of regular beer, 5 oz of wine, or 1.5 oz of liquor. The possible score range for AMED was 0 to 9, with higher scores representing a closer resemblance to the Mediterranean diet. Consumption of each food group was stable across time except for a trend toward a decrease in alcohol and red/processed meat intake [23].

Follow-up and outcome

The vital status of participants was ascertained through a combination of active and passive follow-up methods. During the active follow-up, face-to-face interviews with patients were conducted to gather updated information. For the passive follow-up, health outcomes and medical records for all deceased participants were acquired from the Liaoning Province Center for Disease Control and the information system at Shengjing Hospital. The main outcome of this study was overall survival (OS). Survival time was defined as the interval between the histological diagnosis of OC and the date of death from any cause or the date of last follow-up (February 16, 2023) for patients who were still alive.

Statistical analysis

Continuous variables were shown as mean with standard deviation (SD) or median with interquartile (IQR), whereas categorical variables were presented as numbers with percentages. The discrepancy in clinical and demographic featured by tertiles of the pre-diagnosis and post-diagnosis AMED scores was evaluated using the Chi-square test for categorical variables and one-way analysis of variance or the Kruskal–Wallis test for continuous variables. The Kaplan–Meier technique was applied to estimate crude survival probabilities and plot crude survival curves. Furthermore, we undertake a nonlinear analysis to examine the collinearity among the covariates, thereby enhancing the robustness of our statistical assessments.

The Cox proportional hazards regression model was used to assess the associations of the pre-diagnosis and post-diagnosis AMED with OS by calculating the hazard ratios (HRs) and 95% confidence intervals (CIs). The proportional hazards assumption was tested by adding an interaction term between each activity variable and log survival time. If the proportional risk hypothesis is not satisfied (P < 0.05), the time-dependent Cox regression model is used. The AMED score was categorized into tertile, with the lowest tertile as a reference. The P values for linear trend were calculated by allocating the median value of each tertile for index scores as a continuous term in Cox regression models. Continuous intakes were also calculated by 1 SD increment of each AMED score. The selection of confounders was based on prior knowledge and directed acyclic graphs (Supplementary Figure S1) [24].

For the analyses of pre-diagnosis and post-diagnosis AMED scores as the exposure, we developed three models. In model 1, we adjusted for age at diagnosis (continuous, years), BMI (continuous, kg/m2), and total energy intake (continuous, kcal/day). In model 2, we further adjusted for education (junior secondary or below, senior high school/technical secondary school, or junior college/university or above), smoking status (yes or no), income (< 5,000, 5,000–10,000 or > 10,000Yuan/month), physical activity (continuous, metabolic equivalent task/hours/week), and menopausal status (yes or no) based on model 1. Model 3 was further adjusted for clinical characteristics, including histological type (non-serous or serous), residual lesions (yes or no), comorbidities (yes or no), and FIGO stage (I-II or III-IV) based on model 2.

To investigate how a change in AMED score before and after OC diagnosis, we divided participants into four groups of changes based on the number of participants in each group: no change or relatively stable (± 5%, reference group), decrease (> 5%), increase (5%-15%) and significantly increase (> 15%). Additionally, a cross-classified change model was utilized to categorize pre-diagnosis and post-diagnosis AMED scores into four groups: consistently low intake (reference), consistently high intake, and inconsistent intake [25]. Cox proportional hazard models were then employed to analyze the correlation between changes in AMED score and OS. In the models, we adjusted for the same covariates and additionally adjusted for the initial AMED score (tertile), change in total energy intake (quintile), change in BMI (quintile), change in smoking status (categorical), and change in physical activity (quintile) [26].

To assess the robustness of our findings, we performed subgroup analyses stratified by the age at diagnosis (≤ 50 and > 50 years), BMI (≤ 24 and > 24 kg/m2), menopausal status (no and yes), histological types (serous and non-serous), FIGO stage (I-II and III-IV), residual lesions (no and yes), and parity (≤ 1 and > 1). The additive and multiplicative interactions were both evaluated between the AMED score and these stratified variables [27]. Based on the multivariable Cox models, a cross-product term was included to explore the potential multiplicative interactions. The additive interactions were estimated by calculating the relative excess risk due to interaction.

To further analyze and verify the stability of the results, we conducted two sensitivity analyses. First, we excluded patients who died within one year after diagnosis in our cohort to account for potential reverse causation. Second, we calculated the E-value, which is an alternative approach to sensitivity analyses for unmeasured confounding in observational studies [28]. E-value represents how strong would the unmeasured confounding have to be to negate the observed results [28]. The higher the E-value is, the stronger the unmeasured confounding must be to explain the observed association [29]. All statistical analyses were conducted using SAS version 9.4 (SAS Institute, Cary, NC, USA). Two-sided P < 0.05 were considered statistically significant.

Results

We summarized the characteristics of the 560 patients with OC according to their alive and deceased status (Supplementary Table S2). Of these participants, a total of 211 all-cause deaths (37.68%) were recorded during a median of 44.40 months of follow-up (IQR: 26.97–61.37 months). Among the patients who died, the mean (SD) pre-diagnosis and post-diagnosis AMED scores were 27.63 (5.08) and 28.90 (5.04), respectively. For alive patients, the corresponding mean (SD) pre-diagnosis AMED score was 28.06 (4.97), and the post-diagnosis AMED score was 29.46 (5.00).

Table 1 displays the fundamental characteristics of patients with OC, categorized by their pre-diagnosis and post-diagnosis AMED scores. Patients with elevated AMED scores, both pre-diagnosis and post-diagnosis, were predominantly postmenopausal and had extended follow-up durations. Furthermore, those with higher pre-diagnosis AMED scores exhibited higher monthly incomes and were more frequently diagnosed with the serous histological subtype in contrast to those with lower AMED scores. Additionally, patients with heightened post-diagnosis AMED scores demonstrated greater physical activity. The presence of larger residual lesions and advanced FIGO stages were significantly correlated with worse survival, as detailed in Supplementary Table S3. Moreover, Supplementary Figure S2 and S3 graphically illustrates the relationship between both pre-diagnosis and post-diagnosis AMED scores, as well as their variations, and OC survival.

Table 1 General characteristics of patients with ovarian cancer according to pre-diagnosis and post-diagnosis AMED scores
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Table 2 shows the associations between pre-diagnosis and post-diagnosis AMED scores and the OS of patients with OC. The highest tertile of AMED scores was associated with better OS compared with the lowest tertile (pre-diagnosis: HR = 0.59, 95% CI 0.38–0.90, Ptrend = 0.02; post-diagnosis: HR = 0.61, 95% CI 0.41–0.91, Ptrend = 0.01). However, the risk estimating per SD increment in AMED score was significant only in pre-diagnosis (HR = 0.78, 95% CI 0.66–0.92).

Table 2 HRs by AMED scores in ovarian cancer patientsa
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Compared with patients who maintained a relatively stable AMED score (change within 5%), individuals with decreased AMED score (change of more than 5%) from pre-diagnosis to post-diagnosis had a 66% higher all-cause mortality (95% CI 1.11–2.50) (Table 3). For those patients who had increased AMED score (change of more than 15%) from pre-diagnosis to post-diagnosis had a lower risk of all-cause mortality (HR = 0.59, 95% CI 0.38–0.90). In addition, patients with OC who adhered to a high AMED score had a lower risk of all-cause mortality, compared to those with consistently low AMED score (HR = 0.47, 95% CI 0.31–0.70) (Table 4).

Table 3 HRs by AMED score changes in ovarian cancera
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Table 4 HRs by AMED score change groups in ovarian cancer†
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In the subgroup analyses stratified by demographical and clinical characteristics, the results agreed with the main findings. No significant interactions were found except for pre-diagnosis age subgroups (P = 0.01 for additive interaction) (Fig. 2). Upon conducting a comprehensive nonlinear analysis, we found no evidence of collinearity among the covariates, ensuring the validity and reliability of our statistical model.

Fig. 2
figure 2

Subgroup analyses of demographical and clinical characteristics for the associations between pre-diagnosis and post-diagnosis Alternate Mediterranean Diet scores and overall survival among patients with ovarian cancer. HR (95% CI) shows the results for the highest tertile compared to the lowest tertile. The Pre-diagnosis model was adjusted for age at diagnosis, pre-diagnosis body mass index, pre-diagnosis total energy intake; pre-diagnosis cigarette smoking, education, income, pre-diagnosis physical activity, menopausal status; histological type, FIGO stage, comorbidities, and residual lesions. The Post-diagnosis model was adjusted for age at diagnosis, post-diagnosis body mass index, post-diagnosis total energy intake, post-diagnosis cigarette smoking, education, income, post-diagnosis physical activity, menopausal status, histological type, FIGO stage, comorbidities, and residual lesions. CI, confidence interval; FIGO, The International Federation of Gynecology and Obstetrics; HR, hazard ratio. aIndicated P-value for multiplicative interaction. bIndicated P-value for additive interaction

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In the sensitivity analyses, an initial 1-year lagged analysis was conducted. The directional consistency of these results largely aligned with the main findings, though not all demonstrated statistical significance (Supplementary Table S4). Additionally, E-values were computed to assess the potential effect of unmeasured confounders. The calculated E-values were 3.01 for the pre-diagnosis AMED score and 3.27 for the post-diagnosis AMED score (Supplementary Table S5). These values suggested that the observed associations may result from residual confounding if unmeasured variables exhibit relative risks with OC survival and AMED scores at least as strong as the E-values.

Discussion

Main findings

This study was the initial report of the association between pre-diagnosis and post-diagnosis adherence to AMED and OS among patients with OC within the context of a prospective cohort study. The findings indicated that higher pre-diagnosis and post-diagnosis AMED scores were correlated with improved OS. Moreover, our results suggested that consistent adherence to a high-AMED diet pre-diagnosis and post-diagnosis was linked with a reduction in OS compared with maintaining low-AMED diet scores.

The AMED score has been reported to be linked to an increased risk of all-cause mortality and poor prognosis across various cancer types in some prospective cohorts [11, 30,31,32]. Thus far, scarce evidence has evaluated the relationship between AMED scores and OC survival. Notably, only one cohort study probed the relationship between the high pre-diagnosis AMED score and low OC risk as well as better survival, which was consistent with the results of our study [12]. This study was conducted within the NIH-AARP Diet and Health Study. Better pre-diagnosis diet quality according to the AMED (Quintile 5 vs Quintile 1: HR = 0.68, 95% CI 0.53–0.87) was associated with lower all-cause mortality. Furthermore, some studies have reported the association between the AMED score and cause-specific mortality [33]. Findings from the Nurses' Health Study and the Health Professionals Follow-up Study showed that compared the highest with the lowest quintiles, the pooled multivariable-adjusted HRs of total mortality were 0.82 (95% CI 0.79–0.84) for AMED score [8]. In addition, a prospective cohort study included 23,212 individuals in the National Health and Nutrition Examination Survey from 2005 to 2014 showed that participants with lower AMED had a significantly higher risk of all-cause mortality (HR = 2.16, 95% CI 1.49–3.13) [30].

Additionally, some studies have explored the association between the AMED score and the incidence of OC [34]. A prospective cohort study conducted within the Nurses’ Health Study, which included 121,700 registered female participants, found no association between AMED score and OC risk [13]. In contrast, a report from the Netherlands Cohort Study indicated middle compared with low AMED score was significantly associated with a reduced OC risk (HR = 0.85, 95% CI 0.36–0.99) [4].

AMED may impact OC survival directly through biological pathways and indirectly through adherence to chemotherapy [35]. The cancer-preventive effect of the AMED seems biologically plausible. The high intake of dietary antioxidants in the AMED (e.g., polyphenols and vitamins from plant foods and olive oil) and the resulting higher total antioxidant capacity that has been associated with adherence to this dietary pattern may defend the body against the DNA-damaging effects of free radicals and other oxidants [36, 37]. Moreover, the anti-inflammatory effects of polyphenols and the favorable fatty acid profile of the AMED (high in anti-inflammatory omega-3 polyunsaturated fatty acids) may reduce inflammation [38]. Several additional mechanisms have been proposed for the cancer-preventive effect of the AMED, which were among others related to body weight regulation and the low consumption of red and processed meats [37]. Certain fermented foods, such as yogurt and kimchi, contain probiotics and prebiotics that help maintain gut microbiome balance [39]. Additionally, nutrients like folic acid and vitamin B12 play critical roles in DNA methylation, potentially affecting gene methylation status through dietary intake [40]. This alteration in gene expression patterns may influence cancer initiation and progression. In clinical practice, doctors can develop personalized nutritional recommendations based on the specific circumstances and health status of patients. At the same time, doctors can also make appropriate adjustments according to patients' dietary preferences and lifestyle habits to improve patient compliance and satisfaction.

Strengths and limitations

There are several strengths in our study. Firstly, compared with previous studies, the present study had relatively larger sample size to investigate the association between pre-diagnosis and post-diagnosis diet quality, as well as their changes and the prognosis of OC. Secondly, Our FFQ encompasses a broad range of food categories that participants may consume, including staple foods, non-staple foods, snacks, beverages, and other categories [18]. It has been tailored and optimized for individuals from different regions and cultural backgrounds. Additionally, the questionnaire accounts for the impact of seasonal and cultural factors on dietary habits, resulting in a more comprehensive tool suitable for the Chinese population. To minimize recall bias, we shortened the recall period, provided detailed food lists and portion size guidance, and utilized a standardized methodology for processing FFQ data, thereby reducing error and bias [16, 41]. The robustness of the FFQ is maintained through continuous optimization and refinement, leading to a more accurate assessment of dietary intake among respondents. In addition, our pre-diagnosis data were collected at the time of the patients' initial diagnosis and hospital admission, which involved summarizing their previous eating habits. The post-diagnosis data were then collected 12 months after the diagnosis. Since this study was a non-intervention study, compliance issues do not arise. Further intervention trials are needed to better monitor and enhance adherence dietary therapy in their studies. Thirdly, unlike previous studies that only focused on the pre-diagnosis AMED score, we also focused on the role of post-diagnosis and changes from pre-diagnosis to post-diagnosis in OC survival. In addition, dietary and covariate data were collected multiple times throughout baseline and follow-up, which allows us to use long-term and thus reduce within-person variation. Additionally, the consistency of results from sensitivity analyses suggests that our findings are robust. Lastly, the detailed data on numerous exposures, including demographic, reproduction, and clinical characteristics factors, allowed us to adjust for multiple confounding factors and reduce potential confounding bias.

Potential limitations should be considered when interpreting our findings. First, self-reported dietary intake by FFQ is prone to recall bias and other types of error [42]. To mitigate these biases, we implemented stringent enrollment criteria, enrolling only patients who had been newly diagnosed with OC to complete the questionnaire. Second, AMED scores were originally developed for chronic conditions rather than cancer [43]. We utilized AMED scores to evaluate diet quality in patients with OC, which could introduce potential bias. Nonetheless, several studies have investigated the associations between AMED scores and the risk or prognosis of cancer [11, 32, 43]. Third, the study's generalizability was constrained because participants diagnosed with OC were recruited exclusively from a single tertiary hospital in China. Nevertheless, it was pertinent to note that the Shengjing Hospital of China Medical University, where the study was conducted, stands as a large, contemporary, general, and digitalized medical institution. The Department of Obstetrics and Gynecology within this hospital comprised 14 wards, accommodating over 850 beds. Fourth, although we adjusted for many potential confounders and accounted for changes in the covariates, we were not able to rule out the influence of residual and unmeasured confounding in this observational study. Whereas, we conducted an E-value calculation to quantify the potential impact of unmeasured confounders, which suggested that those unmeasured confounders may not significantly influence the conclusions [29]. Lastly, we failed to explore the impact of changes in dietary quality on the progression-free survival of OC in our study. However, evidence has suggested that progression-free survival might be similar to OS due to the poor prognosis and short post-progression survival period of OC [44].

Conclusion

Evidence from our prospective cohort study suggested a correlation between pre-diagnosis and post-diagnosis adherence to high AMED scores and improved OS in OC survivors. Moreover, patients maintaining high AMED scores demonstrated improved OS compared to those with consistently low scores. To validate these findings, further research involving extended follow-up periods and larger cohorts was recommended.

Availability of data and materials

All underlying data is available on reasonable request to the corresponding authors.

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Acknowledgements

The authors would like to thank the OOPS study participants and staff for their valuable contribution to this research.

Funding

This work was supported by the National Key Research and Development Program of China (No. 2022YFC2704205 to Wu QJ), the Natural Science Foundation of China (No. 82073647 and No. 82373674 to Wu QJ and No.82103914 to Gong TT), Outstanding Scientific Fund of Shengjing Hospital (Q-JW).

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Author notes

  1. Yu-Han Chen, Rui-Han Bao, Jia-Cheng Liu, and Jia-Xin Liu have contributed equally to this work.

Authors and Affiliations

  1. Department of Obstetrics and Gynecology, Shengjing Hospital of China Medical University, Shenyang, China

    Yu-Han Chen, Rui-Han Bao, Jia-Cheng Liu, Jia-Nan Sun, Qian Xiao, Sha Ni, Meng Luan, Qi-Jun Wu & Ting-Ting Gong

  2. Department of Epidemiology, School of Public Health, China Medical University, Shenyang, China

    Yu-Han Chen, Xiao-Ying Li & Qi-Jun Wu

  3. School of Undergraduate, China Medical University, Shenyang, China

    Rui-Han Bao & Xiao-Ying Li

  4. Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, Shenyang, China

    Jia-Xin Liu, Dong-Hui Huang & Qi-Jun Wu

  5. Key Laboratory of Precision Medical Research on Major Chronic Disease, Shengjing Hospital of China Medical University, Shenyang, China

    Jia-Xin Liu, Dong-Hui Huang & Qi-Jun Wu

  6. Cancer Epidemiology Division, Population Sciences in the Pacific Program, University of Hawaii Cancer Center, University of Hawaii at Manoa, Honolulu, HI, USA

    Lang Wu

  7. Medical Insurance Office, Shengjing Hospital of China Medical University, Shenyang, China

    Qian Xiao

  8. NHC Key Laboratory of Advanced Reproductive Medicine and Fertility (China Medical University), National Health Commission, Shenyang, China

    Qi-Jun Wu

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  1. Yu-Han Chen
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Contributions

Y-HC, R-HB, SN, ML, Q-JW, and T-TG contributed to the study design. Y-HC, R-HB, SN, ML, Q-JW, and T-TG collection of data. Y-HC, R-HB, J-CL, J-XL, and J-NS analysis of data. Y-HC, R-HB, J-CL, J-XL, J-NS, WL, D-HH, X-YL, QX, SN, ML, Q-JW, and T-TG wrote the first draft of the manuscript and edited the manuscript. All authors read and approved the final manuscript. Y-HC, R-HB, J-CL, and J-XL contributed equally to this work.

Corresponding authors

Correspondence to Sha Ni, Meng Luan, Qi-Jun Wu or Ting-Ting Gong.

Ethics declarations

Ethics approval and consent to participate

This prospective study was approved by the Institutional Review Board of the Ethics Committee of Shengjing Hospital of China Medical University. At enrollment, each participant provided written informed consent for participation, collection and use of data for health research before participation. The study was performed in accordance with the Declaration of Helsinki.

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The authors declare no competing interests.

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Chen, YH., Bao, RH., Liu, JC. et al. Association between pre-diagnosis and post-diagnosis Alternate Mediterranean Diet and ovarian cancer survival: evidence from a prospective cohort study. J Transl Med 22, 860 (2024). https://doi.org/10.1186/s12967-024-05653-2

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Journal of Translational Medicine

ISSN: 1479-5876

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