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Proactive use of PROMs in ovarian cancer survivors: a systematic review



The use of patient reported outcome measures (PROMs) has increased during the past decade, and the focus on how to use them has resulted in a more proactive application. Studies have shown that proactive use of PROMs during treatment improves patient-clinician communication, leads to better symptom management and may prolong survival among advanced cancer patients. Ovarian cancer is a serious disease in which the majority of patients experience recurrence during the follow-up period and suffer from a number of severe symptoms from underlying disease. This systematic review was conducted to assess the evidence on the proactive use of PROMs as a dialogue tool during follow-up of ovarian cancer patients.


The following databases were searched for relevant literature; PubMed, EMBASE, CINAHL, and the Cochrane Library. The search was conducted in April 2019 without any filters or limits. A total of 643 publications were identified, and 48 studies were found to be potentially eligible. Of the 48 papers, none met the final inclusion criterion of using PROMs proactively as a dialogue tool for ovarian cancer patients during follow-up.


Studies have shown that PROMs can identify otherwise undetected symptoms. Using PROMs proactively during the consultation has been shown to improve symptom management for patients with some other types of cancer. However, we found no studies that had examined the proactive use of PROMs during follow-up of ovarian cancer patients. Future studies should evaluate if the proactive use of PROMs could facilitate a more individualized and more effective follow-up program tailored to the ovarian cancer patient’s needs and preferences.


Worldwide, every year 240,000 women are diagnosed with fallopian tube, primary peritoneal, or ovarian cancer (OC), often in advanced stage with approximately 152,000 dying from the disease. This makes OC the leading cause of gynecological cancer-related deaths. Generally, the initial treatment is extensive surgery and chemotherapy to which most patients respond well. Nevertheless, about 80% of these tumors will recur within a few years after primary treatment and treatment of recurrence is rarely curative [1].

After treatment, most patients enter a five-year follow-up (FU) program, including routine clinical visits, imaging, physical examination, and measurement of the cancer biomarker CA125. The primary purpose of FU is early detection of recurrence, but there is no evidence that routine FU increases survival [2]. It may provide reassurance, but for some routine FU may induce anxiety and fear of recurrence [3]. The literature is sparse on this matter in OC patients which further highlights the need for research on individualized follow up plans based on patient needs and preferences [3, 4].

Patient Reported Outcome Measures (PROMs) are defined as “any report of the status of a patient’s health condition that comes directly from the patient, without interpretation of the patient’s response by a clinician or anyone else”. Patient reported outcomes can be measured by means of standardized and validated questionnaires designed for self-completion by patients or by interview [5]. There are several types of PROMs; generic and disease-specific. Generic PROMs are designed to collect data across disease groups, whereas disease-specific PROMs are designed to collect data on outcomes of specific conditions or diagnoses [6]. Some PROMs combine generic and disease-specific elements to capture a broad assessment of the patient’s health status. PROMs can be used to obtain information on physical, emotional, social, sexual, and cognitive functioning besides evaluating side effects or late effects, global health status, and quality of life (QoL). They are often used in clinical trials to monitor health status and QoL before, during, and after treatments to measure patient-related, subjective outcomes secondary to primary endpoints such as survival.

During the past decade, there has been increased interest in using PROMs in routine practice to monitor patient symptoms during treatment. Their use for clarifying patient needs and monitoring late side effects in long-term survivors has received less attention [7]. Evidence from various cancer diagnoses suggests that the use of PROMs during a clinical visit may improve clinician-patient communication by focusing on issues of greater concern to the patient without prolonging the visit [8]. There is also evidence that clinicians often underestimate late side-effects [9, 10]. Use of PROMs as a dialogue tool, alongside blood samples and imaging, may provide clinicians with more valid and comprehensive knowledge of the patient’s problems [11]. A recent study suggested that active use of PROMs during advanced cancer treatment may even prolong survival [12].

We were specifically interested in the potential use of PROMs to improve follow-up care for ovarian cancer survivors. We therefore undertook a systematic review to determine what is already known about proactive use of PROMs as a dialogue tool during follow-up of these patients.


Data sources and search strategy

We conducted a systematic review to assess the proactive use of PROMs as a dialog or screening tool during follow-up of patients after completion of active treatment (e.g. surgery and chemotherapy) for OC. The review was conducted according to Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) [13, 14].

During April 2019 a systematic search was conducted by author AK searching the following databases: PubMed, CINAHL, EMBASE, and the Cochrane Library. Relevant articles published between 1974 to April 2019 were identified. Search strategy in PubMed combining Mesh term “Ovarian Neoplasms”, “Patient Reported Outcome Measures”, “Patient Outcome Assessment”, “Health Care Surveys” and key words “Ovarian Cancer”, “ovarian neoplasms”, “patient outcome assessment” and “patient reported outcome”.

The search terms derived after advice from a research librarian and an advisory group including all co-authors who also helped identify additional “grey literature” of relevance to the research question. No filters were applied. The search strategy for databases PubMed, EMBASE, CINAHL and The Cochrane Library is available in Additional file 1. Titles and abstracts of studies retrieved from the search were screened by AK. Reference lists were manually screened to identify additional papers.

Study selection

Articles were considered eligible if the study participants were OC patients and the proactive use of one or more PROMs during FU was involved. Proactive use of a PROM is defined as data reported by a patient, presented to the clinical staff, and used actively during the consultation as a dialogue tool between patient and clinician.

Studies describing the development of PROMs or PROMs used as a primary or secondary outcome in clinical trials were excluded. Studies were also excluded if PROMs were used to assess the eligibility of patients for chemotherapy, or if they were used to retrospectively identify coping strategies or late side effects with no proactive use.

Review papers were examined for potentially eligible studies that might have been missed in the search strategy. Studies involving multiple cancer sites were excluded if data on OC were not presented separately.

Identification of relevant articles

The titles and abstracts of all retrieved papers were evaluated to determine the relevance of the study. Full texts were retrieved and examined in case the abstract alone did not provide sufficient information.

Data extraction

All potentially eligible studies were screened by reviewer AK. Data were extracted on publication details (author, year and country of study, study design, intervention, and sample size) and all PROM-specific data (type of PROM, how and when used) were entered into a pre-designed form.


The search led to the identification of 643 studies, and after removal of duplicates a total of 337 abstracts were selected for detailed examination (Fig. 1). Forty-eight titles/abstracts met the initial selection criteria and full texts of these were obtained for the assessment of eligibility.

Fig. 1

Flow diagram for search and selection process

Data extraction was performed on the 48 potentially eligible studies, none of which met the final inclusion criterion of using PROMs proactively as a dialogue tool in the follow-up care of OC patients. These papers were excluded for the following reasons: literature review on the use of PROMs (n = 10); description of PROM development, papers showing OC data combined with other cancers, and PROMs used to evaluate a specific intervention (n = 19); surveys investigating clinical staff’s opinion regarding the use of PROMs (n = 3); studies where PROMs were used to assess the patient’s perspective on QoL, or for obtaining prognostic information on life expectancy where the data collected were not used proactively in the care of individual patients (n = 16). The search and selection process is shown in Fig. 1. Characteristics of the studies and reason for exclusion are summarized in Table 1.

Table 1 Characteristics of studies and reasons for exclusion

We found no studies that proactively used PROMs during follow-up care after ovarian cancer treatment and therefore no qualitative synthesis was applied.


We searched for studies involving the proactive use of PROMs during follow-up after ovarian cancer treatment but found none. Most studies identified were trials evaluating the effect of specific interventions of OC. PROMs have traditionally been used in observational studies and clinical trials to measure the long-term effect of an intervention or to capture toxicity of new therapies. For some other types of cancer the application of PROMs is progressing from being purely a research tool to monitor side effects in clinical trials, to being used proactively in clinical practice for monitoring symptoms during treatment. By incorporating patients’ assessments and priorities in care management it has revealed a higher frequency of unmet needs that otherwise might have been un-recognized [3, 10, 61].However, we found no evidence that this application of PROMs has been tested with OC patients.

de Rooij et al. performed a randomized trial aiming to assess long-term impact of an automatically generated Survivorship Care Plan (SCP) in ovarian cancer patients. The author found that ovarian cancer patients provided with a SCP did not report increased satisfaction with information provision or care [45]. This highlights that optimal follow up plans should be individualized and tailored for each patient and not a automatically pre-defined tool for all patients.

A recent study has shown that pro-active use of PROMs during treatment improves the QoL of cancer patients [56]. Detmar et al. conducted a randomized clinical trial with patients receiving palliative chemotherapy for different cancer types. Incorporating PROM assessments into clinical practice during treatment and actively using them during the consultation improved patient-clinician communication with the potential to increase the awareness of patient needs [23]. The majority of participants were breast cancer patients receiving first line palliative chemotherapy. This population represents a group with a poor prognosis. These findings were supported by those from a randomized clinical trial involving 766 patients with solid tumors assessed by PROMs during active cancer treatment. Routine collection of PROM data was associated with improved survival by a median of 5 months, suggesting that proactive monitoring helps the clinician to intervene before symptoms cause complications [12]. The participants were recruited between 2007 and 2011, and they had different metastatic cancer types (mainly genitourinary cancer), with a poor prognosis. Such a long timeframe for enrollment may have involved a change of treatment, which could have impacted on survival and burden of symptoms. However, the patients completing PROMs received chemotherapy for a longer period than those receiving usual care. This illustrates the potential of PROMs to detect otherwise unrecognized symptoms during treatment in order to prevent serious events at a later stage.

Hansen et al. found that cancer patients experienced a variety of unmet needs during treatment but also during follow-up, and highlights that the patients indicated that they did not received the support that they needed during follow-up. Unmet needs have an important influence on QoL and PROMs used as a screening tool may reveal patients’ perceived unmet need. Interventions to reduce these unmet needs could enhance patient’s quality of life [62]. Ploos van Amstel et al. aimed to explore distress and quality of life in ovarian cancer patients’ during and after treatment, with a mean time since surgery of 3.3 years. The authors found that a third of the participants’ expressed distress. Almost half of the patients with distress indicated that they wanted a referral to a professional [63]. Their findings indicate that ovarian cancer survivors undergo distress and experience symptoms years after they have finished treatment. If PROMs were used proactively during follow-up this could potentially address patients’ needs and lead to higher satisfaction and improved QoL.

Velikova et al. found that if PROM results were shared with physicians before the clinical encounter, discussions of symptoms took place more frequently compared with the control group. A third of the patients were diagnosed with gynecologic cancer, and PROMs were primarily used during active treatment. Only 2 (1%) participants completed PROMs during follow up. It is unclear if they had gynecologic cancer and the findings are not presented separately. This study adds weight to the conclusion that good communication between clinician and patient should be central to the management of cancer patients. Further, the improved communication resulted in better QoL and emotional functioning for some patients [10]. Howell et al. also reported that if the QoL score was shared with the clinician before the consultation, the level of discussion on emotional and psychosocial issues increased [64].

Many studies have investigated the QoL of OC survivors, late side effects, coping strategies, and many other outcomes over time. If PROMs are collected and used actively during treatment, a positive effect on patient-clinician communication, improved QoL, and a better symptom management during treatment is described. The current model for FU of OC patients is characterized by pre-scheduled visits and mainly concerns standard procedures without necessarily taking the patients’ needs and preferences into account. Pre-scheduled visits may take place at a time when the patient is asymptomatic and thereby induce false reassurance. The value of the standard approach to FU is uncertain, and it is not evidence based. Because of the poor prognosis of OC patients in case of relapse, it is essential to optimize the FU program to focus on what matters most to the patient. Furthermore, pro-active use of PROMs will help ensure that patients are met on their own premises and that the time spent during the consultation is used to help the patient with the problems that bother them the most.

Although interest in collecting PROMs in clinical trials and using them actively as a screening or dialogue tool during treatment is growing, our literature search shows that unfortunately, there is not much experience with this for the benefit of ovarian cancer patients. If PROMs are used proactively during consultations, the visit can be tailored to match the individual patient’s preferences and needs. This may be a new approach to routine collection of PROMs to improve patient centered care and individualized treatment.

We are aware of the limitations of this review. Although we used a comprehensive search strategy, it is still possible that some studies may have been missed. Also, data extraction was performed by only one reviewer who made all decisions about inclusion and exclusion. Lastly, it should be noted that any studies published after 14th of April 2019 were not considered in this paper.


To our knowledge, no studies have used PROMs as a screening or dialogue tool for ovarian cancer survivors during follow-up. The use of PROMs with these patients may help identify otherwise undetected symptoms and improve the management of late side effects. Proactive use of PROMs during follow-up may enhance patient involvement leading to increased satisfaction with care. We believe there is a strong case for further research into this approach to improve the quality of follow-up care of ovarian cancer survivors.

Availability of data and materials

All data generated during this study are included in this published article in Table 1 and in supplementary material.





Ovarian Cancer


Patient Reported Outcome Measures


Quality of Life


Survivorship Care Plan


  1. 1.

    International Agency for Research on Cancer. Global cancer statistics 2012. . Accessed.

  2. 2.

    Rustin GJ, van der Burg ME, Griffin CL, et al. Early versus delayed treatment of relapsed ovarian cancer (MRC OV05/EORTC 55955): a randomised trial. Lancet (London, England). 2010;376(9747):1155–63.

    Article  Google Scholar 

  3. 3.

    Dahl L, Wittrup I, Vaeggemose U, Petersen LK, Blaakaer J. Life after gynecologic cancer--a review of patients quality of life, needs, and preferences in regard to follow-up. Int J Gynecol Cancer. 2013;23(2):227–34.

    PubMed  Article  Google Scholar 

  4. 4.

    Olesen ML, Hansson H, Ottesen B, Thranov IR, Thisted LB, Zoffmann V. The psychosocial needs of gynaecological cancer survivors: A framework for the development of a complex intervention. Eur J Oncol Nurs. 2015;19(4):349–58.

    PubMed  Article  Google Scholar 

  5. 5.

    FDA. Guidance for Industry Patient-Reported Outcome Measures. Use in medical product development to support labeling claims. Clin FED Regist. 2009;2009:1–39.

    Google Scholar 

  6. 6.

    Coulter A PC, Peters M, Fitzpatrick R. Cancer PROMs: a scoping study. Macmillan Cancer Support; 2015.

  7. 7.

    Lockwood-Rayermann S. Survivorship issues in ovarian cancer: a review. Oncol Nurs Forum. 2006;33(3):553–62.

    PubMed  Article  Google Scholar 

  8. 8.

    Berry DL, Blumenstein BA, Halpenny B, et al. Enhancing patient-provider communication with the electronic self-report assessment for cancer: a randomized trial. J Clin Oncol. 2011;29(8):1029–35.

    PubMed  PubMed Central  Article  Google Scholar 

  9. 9.

    Sepucha KR, Levin CA, Uzogara EE, Barry MJ, O'Connor AM, Mulley AG. Developing instruments to measure the quality of decisions: early results for a set of symptom-driven decisions. Patient Educ Couns. 2008;73(3):504–10.

    PubMed  Article  Google Scholar 

  10. 10.

    Velikova G, Booth L, Smith AB, et al. Measuring quality of life in routine oncology practice improves communication and patient well-being: a randomized controlled trial. J Clin Oncol. 2004;22(4):714–24.

    PubMed  Article  Google Scholar 

  11. 11.

    Hess LMP, Stehman FBMD. State of the science in ovarian Cancer quality of life research: A systematic review. Int J Gynecol Cancer. 2012;22(7):1273–80.

    PubMed  Article  Google Scholar 

  12. 12.

    Basch E, Deal AM, Dueck AC, et al. Overall survival results of a trial assessing patient-reported outcomes for symptom monitoring during routine Cancer treatment. Jama. 2017;318(2):197–8.

    PubMed  PubMed Central  Article  Google Scholar 

  13. 13.

    Liberati A, Altman DG, Tetzlaff J, et al. The PRISMA statement for reporting systematic reviews and meta-analyses of studies that evaluate health care interventions: explanation and elaboration. J Clin Epidemiol. 2009;62(10):e1–34.

    PubMed  Article  Google Scholar 

  14. 14.

    Moher D, Liberati A, Tetzlaff J, Altman DG. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. J Clin Epidemiol. 2009;62(10):1006–12.

    PubMed  Article  Google Scholar 

  15. 15.

    Hess LM, Stehman FB. State of the science in ovarian cancer quality of life research: a systematic review. Int J Gynecol Cancer. 2012;22(7):1273–80.

    PubMed  Article  Google Scholar 

  16. 16.

    Hilpert F, Du Bois A. Patient-reported outcomes in ovarian cancer: are they key factors for decision making? Expert Rev Anticancer Ther. 2018;18(sup1):3–7.

    CAS  PubMed  Article  Google Scholar 

  17. 17.

    Wiering B, de Boer D, Delnoij D. Patient involvement in the development of patient-reported outcome measures: a scoping review. Health Expect. 2017;20(1):11–23.

    PubMed  Article  Google Scholar 

  18. 18.

    Preston NJ, Wilson N, Wood NJ, Brine J, Ferreira J, Brearley SG. Patient-reported outcome measures for use in gynaecological oncology: a systematic review. BJOG. 2015;122(5):615–22.

    CAS  PubMed  Article  Google Scholar 

  19. 19.

    Clarke T, Galaal K, Bryant A, Naik R. Evaluation of follow-up strategies for patients with epithelial ovarian cancer following completion of primary treatment. Cochrane Database Syst Rev. 2014;(9).

  20. 20.

    Kew F, Galaal K, Bryant A, Naik R. Evaluation of follow-up strategies for patients with epithelial ovarian cancer following completion of primary treatment. The Cochrane database of systematic reviews. 2011;(6):Cd006119.

  21. 21.

    Zikos E, Coens C, Quinten C, et al. The added value of analyzing pooled health-related quality of life data: A review of the EORTC PROBE initiative. J Natl Cancer Inst. 2016;108(5).

    PubMed  Article  Google Scholar 

  22. 22.

    Ahmed-Lecheheb D, Joly F. Ovarian cancer survivors' quality of life: a systematic review. J Cancer Surviv. 2016;10(5):789–801.

    CAS  PubMed  Article  Google Scholar 

  23. 23.

    Detmar SB, Muller MJ, Schornagel JH, Wever LD, Aaronson NK. Health-related quality-of-life assessments and patient-physician communication: a randomized controlled trial. Jama. 2002;288(23):3027–34.

    PubMed  Article  Google Scholar 

  24. 24.

    King MT, Stockler MR, O'Connell RL, et al. Measuring what matters MOST: validation of the measure of ovarian symptoms and treatment, a patient-reported outcome measure of symptom burden and impact of chemotherapy in recurrent ovarian cancer. Quality of Life Research: An International Journal of Quality of Life Aspects of Treatment, Care & Rehabilitation. 2018;27(1):59–74.

    Article  Google Scholar 

  25. 25.

    McCorkle R, Jeon S, Ercolano E, Schwartz P. Healthcare utilization in women after abdominal surgery for ovarian cancer. Nurs Res. 2011;60(1):47–57.

    PubMed  PubMed Central  Article  Google Scholar 

  26. 26.

    Meraner V, Gamper EM, Grahmann A, et al. Monitoring physical and psychosocial symptom trajectories in ovarian cancer patients receiving chemotherapy. BMC Cancer. 2012;12:77.

    PubMed  PubMed Central  Article  Google Scholar 

  27. 27.

    Beesley VL, Price MA, Webb PM, et al. Changes in supportive care needs after first-line treatment for ovarian cancer: identifying care priorities and risk factors for future unmet needs. Psycho-oncology. 2013;22(7):1565–71.

    PubMed  Article  Google Scholar 

  28. 28.

    Stewart DE, Wong F, Duff S, Melancon CH, Cheung AM. "what doesn't kill you makes you stronger": an ovarian cancer survivor survey. Gynecol Oncol. 2001;83(3):537–42.

    CAS  PubMed  Article  Google Scholar 

  29. 29.

    Bodurka-Bevers D, Basen-Engquist K, Carmack CL, et al. Depression, anxiety, and quality of life in patients with epithelial ovarian cancer. Gynecol Oncol. 2000;78(3 Pt 1):302–8.

    CAS  PubMed  Article  Google Scholar 

  30. 30.

    Greimel ER, Bjelic-Radisic V, Pfisterer J, et al. Toxicity and quality of life outcomes in ovarian cancer patients participating in randomized controlled trials. Support Care Cancer. 2011;19(9):1421–7.

    PubMed  Article  Google Scholar 

  31. 31.

    Liavaag AH, Dorum A, Fossa SD, Trope C, Dahl AA. Controlled study of fatigue, quality of life, and somatic and mental morbidity in epithelial ovarian cancer survivors: how lucky are the lucky ones? J Clin Oncol. 2007;25(15):2049–56.

    PubMed  Article  Google Scholar 

  32. 32.

    Matei D, Miller AM, Monahan P, et al. Chronic physical effects and health care utilization in long-term ovarian germ cell tumor survivors: a gynecologic oncology group study. J Clin Oncol. 2009;27(25):4142–9.

    PubMed  PubMed Central  Article  Google Scholar 

  33. 33.

    Mercieca-Bebber RL, Price MA, Bell ML, King MT, Webb PM, Butow PN. Ovarian cancer study dropouts had worse health-related quality of life and psychosocial symptoms at baseline and over time. Asia Pac J Clin Oncol. 2017;13(5):e381–8.

    PubMed  Article  Google Scholar 

  34. 34.

    Guidozzi F. Living with ovarian cancer. Gynecol Oncol. 1993;50(2):202–7.

    CAS  PubMed  Article  Google Scholar 

  35. 35.

    Chase DM, Wenzel L. Health-related quality of life in ovarian cancer patients and its impact on clinical management. Expert Rev Pharmacoecon Outcomes Res. 2011;11(4):421–31.

    PubMed  PubMed Central  Article  Google Scholar 

  36. 36.

    Williams LA, Agarwal S, Bodurka DC, Saleeba AK, Sun CC, Cleeland CS. Capturing the patient's experience: using qualitative methods to develop a measure of patient-reported symptom burden: an example from ovarian cancer. J Pain Symptom Manag. 2013;46(6):837–45.

    Article  Google Scholar 

  37. 37.

    Greimel E, Bottomley A, Cull A, et al. An international field study of the reliability and validity of a disease-specific questionnaire module (the QLQ-OV28) in assessing the quality of life of patients with ovarian cancer. Eur J Cancer. 2003;39(10):1402–8.

    CAS  PubMed  Article  Google Scholar 

  38. 38.

    Snyder CF, Aaronson NK. Use of patient-reported outcomes in clinical practice. Lancet (London, England). 2009;374(9687):369–70.

    Article  Google Scholar 

  39. 39.

    Bordlein-Wahl I, Hilpert F, Kohlmann T. Evaluating treatment from the point of view of the patient -PROs (patient-reported outcomes). Onkologie. 2009;32(Suppl 1):18–20.

    PubMed  Article  Google Scholar 

  40. 40.

    Roncolato FT, Gibbs E, Lee CK, et al. Quality of life predicts overall survival in women with platinum-resistant ovarian cancer: an AURELIA substudy. Ann Oncol. 2017;28(8):1849–55.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  41. 41.

    Jensen RE, Snyder CF. PRO-cision medicine: personalizing patient care using patient-reported outcomes. J Clin Oncol. 2016;34(6):527–9.

    PubMed  Article  Google Scholar 

  42. 42.

    Beesley VL, Smith DD, Nagle CM, et al. Coping strategies, trajectories, and their associations with patient-reported outcomes among women with ovarian cancer. Support Care Cancer. 2018;26(12):4133–42.

    PubMed  Article  Google Scholar 

  43. 43.

    Du Bois A, Rochon J, Lamparter C, Pfisterer J. Pattern of care and impact of participation in clinical studies on the outcome in ovarian cancer. Int J Gynecol Cancer. 2005;15(2):183–91.

    PubMed  Article  Google Scholar 

  44. 44.

    Madalinska JB, van Beurden M, Bleiker EM, et al. Predictors of prophylactic bilateral salpingo-oophorectomy compared with gynecologic screening use in BRCA1/2 mutation carriers. J Clin Oncol. 2007;25(3):301–7.

    PubMed  Article  Google Scholar 

  45. 45.

    de Rooij BH, Ezendam NPM, Nicolaije KAH, et al. Effects of survivorship care plans on patient reported outcomes in ovarian cancer during 2-year follow-up - the ROGY care trial. Gynecol Oncol. 2017;145(2):319–28.

    PubMed  Article  Google Scholar 

  46. 46.

    Phillips KA, Haas JS, Liang SY, et al. Are gatekeeper requirements associated with cancer screening utilization? Health Serv Res. 2004;39(1):153–78.

    PubMed  PubMed Central  Article  Google Scholar 

  47. 47.

    Cesario SK, Nelson LS, Broxson A, Cesario AL. Sword of Damocles cutting through the life stages of women with ovarian cancer. Oncol Nurs Forum. 2010;37(5):609–17.

    PubMed  Article  Google Scholar 

  48. 48.

    Keim-Malpass J, Mihalko SL, Russell G, Case D, Miller B, Avis NE. Problems experienced by ovarian Cancer survivors during treatment. J Obstet Gynecol Neonatal Nurs. 2017;46(4):544–54.

    PubMed  PubMed Central  Article  Google Scholar 

  49. 49.

    Oberguggenberger A, Sztankay M, Morscher RJ, et al. Psychosocial outcomes and counselee satisfaction following genetic counseling for hereditary breast and ovarian cancer: A patient-reported outcome study. J Psychosom Res. 2016;89:39–45.

    PubMed  Article  Google Scholar 

  50. 50.

    Stukenborg GJ, Blackhall LJ, Harrison JH, Dillon PM, Read PW. Longitudinal patterns of cancer patient reported outcomes in end of life care predict survival. Support Care Cancer. 2016;24(5):2217–24.

    PubMed  Article  Google Scholar 

  51. 51.

    Rietveld M, Husson O, Vos C, Van De Poll-Franse L, Ottevanger N. Perceived information provision, is it related to supportive care needs? Int J Gynecol Cancer. 2016;26 (Supplement 3:810.

    Article  Google Scholar 

  52. 52.

    Beesley VL, Price MA, Butow PN, Green AC, Olsen CM, Webb PM. Physical activity in women with ovarian cancer and its association with decreased distress and improved quality of life. Psycho-oncology. 2011;20(11):1161–9.

    PubMed  Article  Google Scholar 

  53. 53.

    Greimel E, Bjelic-Radisic V, Nagele E, Bliem B, Tamussino K. Quality of life in patients with ovarian cancer. [German]. Onkologe. 2019;25(2):151–6.

    Article  Google Scholar 

  54. 54.

    Pearman TP, Beaumont JL, Mroczek D, O'Connor M, Cella D. Validity and usefulness of a single-item measure of patient-reported bother from side effects of cancer therapy. Cancer. 2018;124(5):991–7.

    PubMed  Article  Google Scholar 

  55. 55.

    Astrup GL, Hofso K, Bjordal K, et al. Patient factors and quality of life outcomes differ among four subgroups of oncology patients based on symptom occurrence. Acta Oncol. 2017;56(3):462–70.

    PubMed  Article  Google Scholar 

  56. 56.

    Basch E, Deal AM, Kris MG, et al. Symptom monitoring with patient-reported outcomes during routine Cancer treatment: A randomized controlled trial. J Clin Oncol. 2016;34(6):557–65.

    CAS  PubMed  Article  Google Scholar 

  57. 57.

    Anderson RT, Peres LC, Camacho F, et al. Individual, social, and societal correlates of health-related quality of life among African American survivors of ovarian cancer: results from the African American cancer epidemiology study. J Women's Health. 2019;28(2):284–93.

    Article  Google Scholar 

  58. 58.

    Hilarius DL, Kloeg PH, Gundy CM, Aaronson NK. Use of health-related quality-of-life assessments in daily clinical oncology nursing practice: a community hospital-based intervention study. Cancer. 2008;113(3):628–37.

    PubMed  Article  Google Scholar 

  59. 59.

    Shalowitz DI, Schorge JO. Suggestibility of Oncologists' clinical estimates. JAMA oncology. 2015;1(2):251–3.

    PubMed  Article  Google Scholar 

  60. 60.

    Kew FM, Cruickshank DJ. Routine follow-up after treatment for a gynecological cancer: a survey of practice. Int J Gynecol Cancer. 2006;16(1):380–4.

    CAS  PubMed  Article  Google Scholar 

  61. 61.

    Basch E, Artz D, Dulko D, et al. Patient online self-reporting of toxicity symptoms during chemotherapy. J Clin Oncol. 2005;23(15):3552–61.

    PubMed  Article  Google Scholar 

  62. 62.

    Hansen DG, Larsen PV, Holm LV, Rottmann N, Bergholdt SH, Sondergaard J. Association between unmet needs and quality of life of cancer patients: a population-based study. Acta Oncol. 2013;52(2):391–9.

    PubMed  Article  Google Scholar 

  63. 63.

    Ploos van Amstel FKRNM, van Ham MAPCPMD, Peters EJM, Prins JBPM, Ottevanger PBPMD. Self-reported distress in patients with ovarian Cancer: is it related to disease status? Int J Gynecol Cancer. 2015;25(2):229–35.

    PubMed  Article  Google Scholar 

  64. 64.

    Howell D, Molloy S, Wilkinson K, et al. Patient-reported outcomes in routine cancer clinical practice: a scoping review of use, impact on health outcomes, and implementation factors. Ann Oncol. 2015;26(9):1846–58.

    CAS  PubMed  Article  Google Scholar 

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We thank Karin Larsen for linguistic editing of the manuscript.


As a PhD student Anette Stolberg Kargo received funding from The Danish Cancer Society. The funder played no role in the design in the undertaking of the review or in writing the manuscript.

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All authors were a major contributor in writing this manuscript, and all have helped identify additional “gray literature”. All co-authors has read and approved the final manuscript.

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Correspondence to Anette Stolberg Kargo.

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Kargo, A.S., Coulter, A., Jensen, P.T. et al. Proactive use of PROMs in ovarian cancer survivors: a systematic review. J Ovarian Res 12, 63 (2019).

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  • Ovarian cancer
  • Follow-up
  • Patient reported outcome
  • Quality of life