Literature DB >> 26404128

Wait times from diagnosis to treatment in cancer.

Laurie Elit1.   

Abstract

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Mesh:

Year:  2015        PMID: 26404128      PMCID: PMC4620358          DOI: 10.3802/jgo.2015.26.4.246

Source DB:  PubMed          Journal:  J Gynecol Oncol        ISSN: 2005-0380            Impact factor:   4.401


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See accompanying article by Nanthamongkolkul and Hanprasertpong on page 262. Receiving a cancer diagnosis is anxiety provoking. Waiting for definitive treatment for cancer augments this anxiety [1234567]. Waiting for treatment also decreases patient satisfaction with their medical center and results in a poorer quality of life [48]. The underlying concern is whether longer wait times lead to spreading of tumor, the need for more extensive therapy and ultimately poorer survival. There have been studies across cancer types addressing the relationship between wait times and overall survival. Table 1 shows those studies where there is a clear detrimental relationship on survival and those where the relationship is inconclusive [4891011121314151617181920212223242526272829303132333435].
Table 1

Relationship of time from diagnosis to surgical treatment on survival

Clear relationshipUnclear relationship
StudyTimeStudyTime
BladderKulkarni et al. (2009) [13]*40 dayNielsen et al. (2007) [17]
Ayres et al. (2008) [14]3 mo
Lee et al. (2006) [15]3 mo
Gore et al. (2009) [16]12 wk
BreastRichards et al. (1999) [18]3 moBrazda et al. (2010) [12]
Yun et al. (2012) [8]*1 moMcLaughlin et al. (2012) [19] (early stage)
McLaughlin et al. (2012) [19] (late stage)*60 day
CervixNanthamongpkolkul et al. (2015) [35]8 wkUmezu et al. (2012) [20]
Perri et al. (2014) [21]
ColorectalYun et al. (2012) [8]*1 moRamos et al. (2007) [24]
Simunovic et al. (2009) [4]*2 wk
Walsh et al. (2007) [22]2 wk
Zafar et al. (2012) [23]
Currie et al. (2012) [25]
EsophagusKotz et al. (2006) [27]*3, 5, 9 wk
Grotenhuis et al. (2010) [26]
Sharpe et al. (2010) [28]2 wk
Head and neckVan Harten et al. (2015) [11]*15, 30, 60, 75, 90 day
LungYun et al. (2012) [8]*1 moMyrdal et al. (2004) [29]
MelanomaPacifico et al. (2007) [30]2 wk
PancreasYun et al. (2012) [8]1 moRaptis et al. (2010) [31]62 day
ProstateRedaniel et al. (2013) [32]*3, 6 mo
RenalStec et al. (2008) [10]
StomachYun et al. (2012) [8]*1 mo
UterusElit et al. (2014) [9]*12 wkMenczer et al. (1995) [33]4 mo
Matsuo et al. (2015) [34]14, 42, 84 day

*Population based; †Meta-analysis.

With the exception of esophageal cancer, each disease site has studies showing divergent answers as to whether there is a relationship between wait times for surgery and survival. In part this is related to the quality of the studies. All of the studies are retrospective cohort studies that may be single center or population based. Such studies have the risk of confounding and so it is important to conduct multivariate analysis with risk adjustment. Unfortunately, many studies do not have details about stage, or histology which should be included in the model. Duration of follow-up can lead to variation in results. In addition the reason for treatment delay is not always clear (i.e., patient comorbidities impacting the timing of surgery). Single center studies often have small sample sizes which may limit the ability to find a relationship even if one exists. Rather than looking at wait times as a continuous relationship, often the studies look at wait times in a dichotomous variable and so miss an issue. There is a clear relationship between better outcomes (quality of care) in high volume hospitals compared to low volume centers across many cancer types [10]. In many jurisdictions we have seen a displacement of surgical volume to high volume cancer centers [36]. Rising wait times in this setting reflects a compromised ability of the system of care to deal with this volume in terms of availability of resources and efficiencies [9]. Specific stresses are seen in diagnostic (i.e., diagnostic radiology, interventional radiology, pathology) and treatment resources (number of quality oncology surgeons, operating room access, inpatient beds) [489363738]. To compound this, fixed hospital budgets limit capacity and provide little incentive for medical staff to increase production. To deal with this problem, there has been a plea that wait times be considered when formulating national health policy [8]. Profession societies and authorities have set standards which by enlarge focus on 30 days from diagnosis of cancer to treatment [839] and no longer than 8 weeks [4041]. Fast tract programs in Europe, USA, and Canada [91142] promote care pathways to minimize time from diagnosis, staging to treatment. Implementing multidisciplinary tumor boards and joint clinics have also helped. In this journal, Nanthamongkolkul and Hanprasertpong [35] adds to the list of studies in Table 1 showing that in Thailand at a single center, wait times exceeding 8 weeks for surgery in early stage cervical cancer care leads to worse outcomes. This group also shows that in addition to system issues described above, in middle resource countries, long wait times for surgery can be related to additional factors. Rising wait times can reflect issues with inability to pay (co-pay or patient pay systems), poor access to services (i.e., limited human resources like surgical oncologists or limited treatment resources like availability of operating rooms) [89], and poor quality of care (i.e., timely diagnosis through screening, diagnosis and staging investigation) [812].
  39 in total

1.  The 2-week wait referral system does not improve 5-year colorectal cancer survival.

Authors:  A Zafar; T Mak; S Whinnie; M A S Chapman
Journal:  Colorectal Dis       Date:  2012-04       Impact factor: 3.788

2.  Clinical presentation and waiting time targets do not affect prognosis in patients with pancreatic cancer.

Authors:  Dimitri A Raptis; Chris Fessas; Peter Belasyse-Smith; Tom R Kurzawinski
Journal:  Surgeon       Date:  2010-04-02       Impact factor: 2.392

3.  Determinants of treatment waiting times for head and neck cancer in the Netherlands and their relation to survival.

Authors:  Michel C van Harten; Frank J P Hoebers; Kenneth W Kross; Erik D van Werkhoven; Michiel W M van den Brekel; Boukje A C van Dijk
Journal:  Oral Oncol       Date:  2014-12-22       Impact factor: 5.337

4.  The UK Government two-week rule and its impact on melanoma prognosis: an evidence-based study.

Authors:  M D Pacifico; R A Pearl; R Grover
Journal:  Ann R Coll Surg Engl       Date:  2007-09       Impact factor: 1.891

5.  The nocebo effect for women in waiting.

Authors:  Elaine Dietsch; Carmel Davies
Journal:  Collegian       Date:  2007-07       Impact factor: 2.573

6.  Longer wait times increase overall mortality in patients with bladder cancer.

Authors:  Girish S Kulkarni; David R Urbach; Peter C Austin; Neil E Fleshner; Andreas Laupacis
Journal:  J Urol       Date:  2009-08-14       Impact factor: 7.450

7.  Influence of delays to nonemergent colon cancer surgery on operative mortality, disease-specific survival and overall survival.

Authors:  Marko Simunovic; Eddy Rempel; Marc-Erick Thériault; Nancy N Baxter; Beth A Virnig; Neal J Meropol; Mark N Levine
Journal:  Can J Surg       Date:  2009-08       Impact factor: 2.089

8.  Impact of wait times on survival for women with uterine cancer.

Authors:  Lorraine M Elit; Erin M O'Leary; Gregory R Pond; Hsien-Yeang Seow
Journal:  J Clin Oncol       Date:  2013-11-25       Impact factor: 44.544

9.  Do delays between diagnosis and surgery in resectable oesophageal cancer affect survival? A study based on West Midlands cancer registration data.

Authors:  B S Kötz; S Croft; D R Ferry
Journal:  Br J Cancer       Date:  2006-09-12       Impact factor: 7.640

10.  Longer waiting times for early stage cervical cancer patients undergoing radical hysterectomy are associated with diminished long-term overall survival.

Authors:  Kulisara Nanthamongkolkul; Jitti Hanprasertpong
Journal:  J Gynecol Oncol       Date:  2015-09-23       Impact factor: 4.401

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  1 in total

1.  Association between complementary and alternative medicine use and prolonged time to conventional treatment among Thai cancer patients in a tertiary-care hospital.

Authors:  Adit Chotipanich; Chulaporn Sooksrisawat; Benjamabhon Jittiworapan
Journal:  PeerJ       Date:  2019-06-14       Impact factor: 2.984

  1 in total

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