Factors Related to Accurate Clinicians’ Prediction of Survival: An International Multicenter Study in East Asia

doi:10.21203/rs.3.rs-4176298/v1

Purpose:

Recent guidelines for prognostic evaluation recommend clinicians’ prediction of survival (CPS) for survival prediction in patients with advanced cancer. However, CPS is often inaccurate and optimistic. Studies on factors associated with overestimation or underestimation of CPS are limited. We aimed to investigate the factors associated with overestimation and underestimation of CPS in patients with far advanced cancer.

Methods:

The current study was a secondary analysis of an international multicenter prospective cohort study, which enrolled newly admitted patients with advanced cancer in palliative care units (PCUs) in Japan, Korea, and Taiwan. We obtained the temporal CPS at enrollment and performed multivariate logistic regression analysis to identify the factors associated with underestimation and overestimation.

Results:

A total of 2571 patients were assessed and admitted in 37 PCUs between January 2017 and September 2018. Older age (adjusted odds ratio [aOR] 1.01; 95% confidence interval [CI] 1.01–1.02; P < 0.01) and reduced oral intake (aOR 0.68; 95% CI 0.51–0.89; P < 0.01) were identified as significant factors associated with underestimation. Dyspnea (aOR 1.28; 95% CI 1.06–1.54; P = 0.01) and hyperactive delirium (aOR 1.34; 95% CI 1.05–1.72; P = 0.02) were identified as significant factors associated with overestimation.

Conclusion:

Older age was related to underestimation while dyspnea and hyperactive delirium were related to overestimation of CPS. However, reduced oral intake was less likely to lead to underestimation.

Prognostication

clinicians’ prediction of survival

advanced cancer

palliative care unit

Prognostic information is essential for patients with advanced cancer. Patients, their families, and health care professionals need accurate prognostic information to decide appropriate future care and discuss what is most important for patients with short life expectancy [1]. The recent guideline for prognostic evaluation recommends clinician predictions of survival (CPS) as the most important prognostic indicator for patients with advanced cancer [2]. Although CPS is an easy and quick prognostic tool, it is often inaccurate and optimistic. A systematic review reported that the accuracy of CPS in palliative care ranged between 23% and 73% [3]. Thus, clinicians should be aware of CPS’s tendency to overestimate survival.

To date, several factors have been known to affect the accuracy of CPS. A study showed that teaching prognostication skills to less experienced health care professionals influenced CPS accuracy [4]. The Karnofsky Performance Scale (KPS) [5] and presence of confusion [6] are related to accurate formulation of CPS. However, studies investigating the factors associated with overestimation or underestimation of CPS are lacking.

The aim of this study was to investigate the factors associated with overestimation and underestimation of CPS in inpatients with advanced cancer admitted to palliative care units (PCUs) in Japan, Korea, and Taiwan. We hypothesized that identifying the factors would be helpful for clinicians to formulate an accurate CPS.

Participants

This study was a secondary analysis of an international multicenter prospective cohort study. The original study—East Asian collaborative cross-cultural Study to Elucidate the Dying process (EASED), had aimed to examine the dying process and end-of-life care of patients with advanced cancer in PCUs in Japan, Korea, and Taiwan. The present study consecutively enrolled eligible patients newly admitted to the participating PCUs during the study period. The inclusion criteria were as follows: (1) adults aged ≥ 18 years in Japan and Korea and ≥ 20 years in Taiwan, (2) patients diagnosed with locally extensive cancer or cancer with any metastasis, and (3) patients newly admitted to a participating PCU. The exclusion criteria were as follows: (1) scheduled discharge within 1 week and (2) refusal of the patient or the patient’s family to enroll in the study.

Data collection

On admission, the responsible palliative care clinicians prospectively recorded all variables on structured data collection sheets. Discharged patients were followed up for 6 months after PCU admission in Japan and Taiwan, and 6 months after PCU discharge in Korea. Death was defined as all deaths inside or outside the PCUs. Survival time was calculated by subtracting the date of admission from the date of death (i.e., death date minus admission date in death cases, or last follow-up date minus admission date in patients who were alive at follow-up). Patients who were alive at the last follow-up were considered censored data.

Measurements

Temporal CPS at enrollment was obtained using the following question: “How long (in days) do you think this patient will live?”

The following clinician characteristics were recorded: sex, clinical experience (in years), clinical experience in palliative care (in years), and number of patients with advanced cancer treated in a year.

Palliative physicians recorded the patients’ baseline data, including age, sex, primary cancer site, metastatic site (liver, lung, and/or central nervous system), ascites (present or absent), pleural effusion (present or absent), bowel obstruction (present or absent), hydration (mL/day), hyperactive delirium, and KPS [7].

Several symptoms, including oral intake, dyspnea, fatigue, drowsiness, and leg edema were documented. Oral intake was categorized as follows: 0, normal; 1, reduced but more than mouthfuls; or 2, less than mouthfuls. Dyspnea was scored as follows: 0, normal; 1, exertional only; or 2, at rest. Patients with scores of 1–2 were considered as having dyspnea in our study. The Integrated Palliative Outcome Scale (IPOS) was used to measure patients’ symptoms, including fatigue and drowsiness, as follows: 0, not at all; 1, slightly; 2, moderately; 3, severely; 4, overwhelmingly; and 5, cannot assess because of unconsciousness. Score of 5 was considered as missing value. The Japanese version of IPOS has been reported to be a valid and reliable tool for adult patients with cancer in Japan [8]. The IPOS is currently undergoing validation in Korea. The Taiwanese version of IPOS has been validated and reported at an international symposium (Tohoku Forum for Creativity 2020).

The severity of leg edema was assessed by measuring the depth upon pressing the skin for sufficient time in the area between the upper and lower joints and was categorized as follows: 0, none; 1, mild (< 5 mm); 2, moderate (5–10 mm); and 3, severe (> 10 mm) [9]. Ascites and pleural effusion were scored based on physician examination as follows: 0, physically undetectable; 1, physically detectable but asymptomatic; or 2, symptomatic. Patients with scores 1–2 were considered as having ascites or pleural effusion here. Patients with scores 1–3 were considered as having lower edema. Delirium was evaluated using the 10-item Memorial Delirium Assessment Scale (MDAS), based on item #9 (psychomotor activity): 0, normal or psychomotor hypoactivity; 1, mild; 2, moderate; or 3, severe [10]. Patients with scores of 1–3 were considered as having delirium.

Statistical analysis

First, a descriptive analysis was performed to summarize the baseline and clinical characteristics of the patients and clinicians.

Second, the patients were categorized into groups of “accurate,” “underestimation,” and “overestimation” based on the CPS estimation. We defined “accurate” estimation as CPS within ± 33% of actual survival (AS) [11]. Thus, CPS less than 33% of AS and more than 33% of AS was considered “underestimation” and “overestimation”, respectively.

Third, we performed multivariate logistic regression analysis to identify the factors associated with “underestimation” and “overestimation” compared with “accurate” estimation. We chose the method based on face validity and the biostatistician’s advice. We entered the following variables into the multivariate logistic regression model: age, KPS, oral intake, dyspnea, leg edema, and hyperactive delirium. Statistical significance was set at p value < 0.05. We constructed the multivariate analysis model by selecting a set of confounders between CPS formulation and obtained variables, which was based on the backdoor criterion using a directed acyclic diagram (DAG) drawing the causal network linking the CPS and obtained variables [12–14]. Variables selected as confounders are shown in Supplementary Fig. 1.

All analyses were performed using IBM SPSS Statistics for Windows, version 26.0 (IBM Corp., Armonk, NY, USA).

Ethics

All study procedures for the primary EASED study received approval by the local Institutional Review Boards (IRBs) of all participating institutions in Japan, Korea, and Taiwan. The current study was conducted in accordance with the ethical standards of the Declaration of Helsinki (as revised in 2013). This study followed the ethical guidelines for medical and health research involving human subjects presented by the Ministry of Health, Labor, and Welfare in Japan. For a noninvasive observational study, Japanese law does not require individual informed consent from the participants. Instructions were posted on the ward or institutional website; thus, all Japanese patients were informed that they had the opportunity to decline participation. In Korea and Taiwan, informed consent was obtained from patients or their families (in cases where the patient was incapable of providing consent). The IRBs of the representative institutes in the three sectors approved this secondary analysis: Seirei Mitakahara General Hospital in Japan (Approval No. 16–29), Dongguk University Ilsan Hospital in Korea (DUIH 2017-01-042-009), and National Taiwan University in Taiwan (201611032RIND).

Patient characteristics

From January 2017 to September 2018, a total of 2685 patients with cancer were recruited across 37 PCUs (twenty-two in Japan, eleven in Korea, and four in Taiwan). However, data of only 2638 patients were available because a small portion of data was lost (Japan: 30; Korea: 17). Of these, 55 patients were excluded because of insufficient follow-up data, and 12 were excluded because of missing data on death date. Thus, 2571 (Japan: 1874; Korea: 305; and Taiwan: 392) patients were finally evaluated. Patients’ baseline characteristics compared among the three groups and based on the accuracy of CPS are summarized in Table 1. The study participants included 1332 men and 1239 women. The median survival was 18 days (95% confidence interval [CI]: 16.9–19.1). Among the 2571 patients, 2465 (95.9%) died at six months after discharge. The accurate estimation, overestimation, and underestimation groups included 746 (29.0%), 1261 (49.1%), and 564 (21.9%) patients, respectively.

Clinician characteristics

Table 2 shows the characteristics of 180 clinicians (106 men and 74 women) by country who participated in this study. The clinical and palliative care careers of Taiwanese clinicians were slightly shorter than those of Japanese or Korean clinicians. However, the number of patients per year was the lowest for Japanese clinicians.

Table 1. Baseline characteristics of patients (n=2571)

Characteristics

Total

(n = 2571)

Accurate

(n = 746)

Overestimation

(n = 1261)

Underestimation

(n = 564)

Country

Japan

Korea

Taiwan

1874 (72.9)

305 (11.9)

392 (15.2)

550 (73.7)

92 (12.3)

104 (13.9)

884 (70.1)

173 (13.7)

204 (16.2)

440 (78.0)

40 (7.1)

84 (14.9)

Age (years, mean ± SD)*

71.0 ± 12.7

70.4 ± 12.5

70.8 ± 12.7

72.4 ± 13.0

Sex

Male

Female

1332 (51.8)

1239 (48.2)

398 (53.4)

348 (46.6)

666 (52.8)

595 (47.2)

268 (47.5)

296 (52.5)

Primary cancer site

Lung

Stomach

Esophagus

Colon

Rectum

Small intestine

Peritoneum

Liver/intrahepatic cholangiocarcinoma

Gall bladder/bile duct

Pancreas

Breast

Cervix

Uterine

Ovary

Kidney

Renal pelvis/Ureter

Bladder

Prostate

Lymph node

Blood (leukemia)

Myeloma

Thyroid

Head/neck (excluding thyroid)

Brain

Bone/soft tissue

Thymus

Mesothelioma

Skin

Unknown primary site

Others

438 (17.0)

251 (9.8)

79 (3.1)

205 (8.0)

126 (4.9)

18 (0.7)

15 (0.6)

193 (7.5)

90 (3.5)

259 (10.1)

165 (6.4)

50 (1.9)

37 (1.4)

61 (2.4)

31 (1.2)

41 (1.6)

55 (2.1)

52 (2.0)

41 (1.6)

12 (0.5)

15 (0.6)

11 (0.4)

118 (4.6)

44 (1.7)

28 (1.1)

4 (0.2)

13 (0.5)

15 (0.6)

40 (1.6)

64 (2.5)

119 (15.9)

83 (11.1)

28 (3.8)

68 (9.1)

40 (5.4)

3 (0.4)

47 (6.3)

26 (3.5)

68 (9.1)

45 (6.0)

20 (2.7)

11 (1.5)

21 (2.8)

12 (1.6)

6 (0.8)

17 (2.3)

20 (2.7)

5 (0.7)

2 (0.3)

5 (0.7)

1 (0.1)

33 (4.4)

16 (2.1)

10 (1.3)

1 (0.1)

4 (0.5)

6 (0.8)

9 (1.2)

17 (2.3)

219 (17.3)

119 (9.4)

37 (2.9)

94 (7.5)

59 (4.7)

11 (0.9)

8 (0.6)

104 (8.2)

44 (3.5)

144 (11.4)

85 (6.7)

20 (1.6)

16 (1.3)

34 (2.7)

10 (0.8)

27 (2.1)

23 (1.8)

24 (1.9)

21 (1.7)

6 (0.5)

5 (0.4)

6 (0.5)

58 (4.6)

12 (1.0)

2 (0.2)

6 (0.5)

5 (0.4)

17 (1.3)

33 (2.6)

100 (17.7)

49 (8.7)

14 (2.5)

43 (7.6)

27 (4.8)

4 (0.7)

42 (7.4)

20 (3.5)

47 (8.3)

35 (6.2)

10 (1.8)

6 (1.1)

9 (1.6)

8 (1.4)

15 (2.7)

8 (1.4)

15 (2.7)

4 (0.7)

5 (0.9)

4 (0.7)

27 (4.8)

16 (2.8)

6 (1.1)

1 (0.2)

3 (0.5)

4 (0.7)

14 (2.5)

Metastasis (liver or lung or central nervous system)

Present

Absent

1563 (60.8)

1008 (39.2)

447 (59.9)

299 (40.1)

799 (63.4)

462 (36.6)

317 (56.2)

247 (43.8)

Oral intake

Normal

Reduced but > mouthfuls

≤ mouthfuls

Missing value

497 (19.3)

1285 (50.0)

782 (30.4)

7 (0.3)

136 (18.2)

394 (52.8)

213 (28.6)

3 (0.4)

223 (17.7)

625 (49.6)

410 (32.5)

3 (0.2)

138 (24.5)

266 (47.2)

159 (28.2)

1 (0.2)

Dyspnea

No

Yes (exertional or at rest)

Missing value^*

1496 (58.2)

1064 (41.4)

11 (0.4)

455 (61.0)

288 (38.6)

3 (0.4)

684 (54.2)

570 (45.2)

7 (0.6)

357 (63.3)

206 (36.5)

1 (0.2)

Fatigue

Present (IPOS 1-4)

Absent (IPOS 0)

Missing value (IPOS 5)

2216 (86.2)

350 (13.6)

5 (0.2)

660 (88.5)

84 (11.3)

2 (0.3)

1093 (86.7)

166 (13.2)

2 (0.2)

463 (82.1)

100 (17.7)

1 (0.2)

Drowsiness

Present (IPOS 1-4)

Absent (IPOS 0)

Missing value (IPOS 5)

1717 (66.8)

849 (33.0)

5 (0.2)

502 (67.3)

242 (32.4)

2 (0.3)

854 (67.7)

405 (32.1)

2 (0.2)

361 (64.0)

202 (35.8)

1 (0.2)

Leg edema (edema of lower extremities)

Present (Mild-Severe)

Absent

Missing value

1290 (50.2)

1275 (49.6)

6 (0.2)

366 (49.1)

378 (50.7)

2 (0.3)

676 (56.6)

582 (46.2)

3 (0.2)

248 (44.0)

315 (55.9)

1 (0.2)

Ascites

Present (detectable or symptomatic)

Absent (undetectable)

Missing value

728 (28.3)

1838 (71.5)

5 (0.2)

207 (27.7)

537 (72.0)

2 (0.3)

400 (31.7)

859 (68.1)

2 (0.2)

121 (21.5)

442 (78.4)

1 (0.2)

Pleural effusion

Present (detectable or symptomatic)

Absent (undetectable)

Missing value

676 (26.3)

1890 (73.5)

5 (0.2)

191 (25.6)

553 (74.1)

2 (0.3)

358 (28.4)

901 (71.5)

2 (0.2)

127 (22.5)

436 (77.3)

1 (0.2)

Bowel obstruction

Present

Absent

Missing value

358 (13.9)

2211 (86.0)

2 (0.1)

123 (16.5)

623 (83.5)

176 (14.0)

1083 (85.9)

2 (0.2)

59 (10.5)

505 (89.5)

Hydration (mL/day, mean ± SD)

432.4 ± 504.4

438.2 ± 520.1

437.0 ± 501.5

414.4 ± 489.8

Hyperactive delirium

Present (Mild–Severe)

Absent (No/hypoactive)

Missing value

460 (17.9)

2110 (82.1)

1 (0.0)

113 (15.1)

633 (84.9)

0

250 (19.8)

1010 (80.1)

1 (0.1)

97 (17.2)

467 (82.8)

0

Karnofsky performance score

70–100

40–60

10–30

Missing value

97 (3.8)

1423 (55.3)

1049 (40.8)

2 (0.1)

30 (4.0)

430 (57.6)

285 (38.2)

1 (0.1)

38 (3.0)

678 (53.8)

544 (43.1)

1 (0.1)

29 (5.1)

315 (55.9)

220 (39.0)

Median survival time (days, 95% CI)

18.0 (16.9–19.1)

25.0 (23.4–26.6)

9.0 (8.4–9.6)

63.0 (55.9–70.1)

Abbreviations: IPOS, Integrated Palliative Outcome Scale; SD, Standard Deviation; CI, Confidence Interval.

Data are expressed as number (%) or mean ± SD.

*’Unconscious patients’ responses are included as missing values.

Table 2

General characteristics of the participating clinicians in the three countries (n = 180)
Characteristics	Japan (n = 87)	Korea (n = 29)	Taiwan (n = 64)
Sex (male)	66 (75.9)	8 (27.6)	32 (50.0)
Career (in years; mean ± SD)	11.2 ± 6.6	12.7 ± 7.8	5.8 ± 3.5
Career in palliative care (in years; mean ± SD)	5.5 ± 5.1	6.8 ± 5.5	2.8 ± 3.1
Number of patients with far advanced cancer seen per year (mean ± SD)	101.3 ± 104.7	129.3 ± 151.9	111.1 ± 141.3
Abbreviations: SD, Standard Deviation.
Data are expressed as number (%) or mean ± SD.

Factors associated with underestimation vs. accurate estimation

Table 3 shows the results of the multivariate analysis. Older age (adjusted odds ratio [aOR] 1.01 per year; 95% CI 1.01–1.02; P < 0.01) and reduced oral intake (aOR 0.68; 95% CI 0.51–0.89; P < 0.01) were identified as significant factors.

Table 3

Results of multivariate analysis: identification of factors associated with underestimation vs. accurate estimation.
Variable
Variable	OR	Adjusted OR	95% CI	P-value
Age	1.01	1.01	1.01–1.02	< 0.01
KPS 10–30 40–60 70–100	0.80 0.76 ref	0.84 0.76 ref	0.48–1.46 0.44–1.3	0.54 0.32
Oral intake Reduced Normal	0.69 ref	0.68 ref	0.51–0.89	< 0.01
Dyspnea Present Absent	0.91 ref	0.91 ref	0.73–1.15	0.43
Leg edema Present Absent	0.81 ref	0.83 ref	0.67–1.04	0.11
Hyperactive delirium Present Absent	1.16 ref	1.16 ref	0.86–1.6	0.34
Abbreviations: OR, odds ratio; CI, confidence interval; KPS, Karnofsky Performance Score; ref, referent group
P-values were obtained by logistic regression analysis.

Factors associated with overestimation vs. accurate estimation

Table 4 demonstrates the results of the multivariate analysis. Dyspnea (aOR 1.28; 95% CI 1.06–1.54; P = 0.01) and hyperactive delirium (aOR 1.34; 95% CI 1.05–1.72; P = 0.02) were identified as significant factors.

Table 4

Results of multivariate analysis: identification of factors associated with overestimation vs. accurate estimation.
Variable
Variable	OR	Adjusted OR	95% CI	P-value
Age	1.00	1.00	0.99–1.01	0.73
KPS 10–30 40–60 70–100	1.51 1.25 ref	1.31 1.17 ref	0.78–2.17 0.71–1.92	0.31 0.54
Oral intake Reduced Normal	1.04 ref	0.95 ref	0.74–1.21	0.66
Dyspnea Present Absent	1.32 ref	1.28 ref	1.06–1.54	0.01
Leg edema Present Absent	1.20 ref	1.17 ref	0.97–1.41	0.09
Hyperactive delirium Present Absent	1.39 ref	1.34 ref	1.05–1.72	0.02
Abbreviations: OR, odds ratio; CI, confidence interval; KPS, Karnofsky Performance Score; ref, referent group
P-values were obtained by logistic regression analysis.

This study showed that older age was related to underestimation while dyspnea and hyperactive delirium were related to overestimation of CPS. On the contrary, reduced oral intake was less likely to lead to underestimation. We identified the associated factors using a parsimonious, multivariate logistic model in 2571 inpatients with advanced cancer admitted to PCUs in three East Asian countries.

The prevalence of frailty increased with age and frailty in older adults was associated with poor survival [15, 16]. Frailty is the age-related decline in function and well-being. Thus, we assumed that clinicians may assess poor general condition in older patients to consider frailty. It is well-known that the illness trajectory of cancer is different from that of frailty [17]. It may be appropriate for clinicians to consider both cancer and frailty trajectories in formulating their CPS for older patients with advanced cancer. In addition, most prognostic tools for week-survival include oral intake as a component [18, 19]. Clinicians often consider oral intake when formulating their CPS. Oral intake can be easily and objectively evaluated in patients; thus, it may contribute to improving the accuracy of the CPS.

Dyspnea has been found to be related to overestimation in previous studies [20, 21]. Considering that dyspnea comprises many prognostic scores [18–21], this finding may need more explanation. Previous studies revealed that dyspnea was associated with the occurrence of sudden unexpected death [22, 23]. Investigators assumed that dyspnea can be a common prodrome to death. Clinicians should consider dyspnea as a more serious sign of shortened life expectancy. Delirium is already a well-known prognostic factor, similar to dyspnea [18]. Thus, clinicians should pay attention not to overestimate survival for patients with hyperactive delirium. Nevertheless, these two manifestations were identified as factors related to overestimation in our study. It may reflect optimistic tendency of clinicians, despite the presence of poor prognostic signs.

This study has the following strengths: it is the first large-scale multicenter and multinational study to investigate the factors associated with the accuracy of CPS in inpatients with advanced cancer. We recognize that this study has some limitations. First, this study was conducted in PCUs. Therefore, the results may not be generalizable to different palliative care settings, such as general wards or home hospice care. Second, most of participating clinicians were palliative care clinicians. Thus, the results might be different for other specialists, such as medical oncologists. Third, the median survival time was relatively short as a few weeks. The CPS may have been affected by the “horizon effect,” which is a phenomenon whereby CPS is more accurate when death is more imminent [24] Fourth, various definitions of the accuracy of CPS exist [25]. Thus, the factors associated with CPS accuracy may vary depending on which definition is applied. Lastly, considering the nature of the secondary analysis of this study, some unmeasured covariates might have been present and may change our results. Thus, future prospective studies are needed to generalize our results.

We demonstrated that older age was associated with underestimation while dyspnea and delirium were associated with overestimation. On the contrary, reduced oral intake was less likely to lead to underestimation. Clinicians should be careful when they prognosticate inpatients with advanced cancer who are older and have dyspnea and delirium. We suggest that clinicians can formulate accurate CPS by taking these factors into account.

Funding

This work was supported in part by a grant-in-aid from the Japanese Hospice Palliative Care Foundation.

Conflicts of interest

All authors have completed the ICMJE uniform disclosure form. The authors have no conflicts of interest to declare.

Data availability

The data that support the findings of this study are available from the corresponding author, Sang-Yeon Suh, upon reasonable request. All authors agree to provide data to the journal for review if needed.

Code availability

Not applicable.

Author contributions

All authors contributed to the study conception and design. Material preparation and data collection and analysis were performed by [Yusuke Hiratsuka, Sang-Yeon Suh, Seok Joon Yoon, Sung-Eun Choi, Sun Hyun Kim, David Hui, Shao-Yi Cheng, Hsien-Liang Huang, Ping-Jen Chen, Jen-Kuei Peng, Masanori Mori, Takashi Yamaguchi, Isseki Maeda, Satoru Tsuneto, and Tatsuya Morita]. The first draft of the manuscript was written by Yusuke Hiratsuka and all authors commented on the previous versions of the manuscript. All authors read and approved the final manuscript.

Ethics approval

The study was conducted in accordance with the Declaration of Helsinki (as revised in 2013). All study procedures for the primary EASED study were approved by the local Institutional Review Boards (IRBs) of all participating institutions in Japan, Korea, and Taiwan. The IRBs of representative institutes in the three sectors approved this secondary analysis: Seirei Mitakahara General Hospital in Japan (Approved No. 16-29), Dongguk University Ilsan Hospital in Korea (DUIH 2017-01-042-009), and National Taiwan University in Taiwan (201611032RIND).

Consent to participate

In accordance with the ethical guidelines for human research of the Ministry of Health, Labor, and Welfare in Japan, patients’ informed consent was waived in Japan because of the completely observational nature of the study. All patients received information on the study through instructions posted on the ward or institutional website and had the opportunity to decline participation. In Korea and Taiwan, informed consent was obtained from patients or their families (in cases where the patient lacked the capacity to provide consent).

Acknowledgments:

We are grateful to Editage (www.editage.co.kr) for proofreading the manuscript for grammar and clarity.

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No competing interests reported.

SupplementaryfigureCPS.docx

Factors Related to Accurate Clinicians’ Prediction of Survival: An International Multicenter Study in East Asia

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Journal Publication

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Abstract

Purpose:

Methods:

Results:

Conclusion:

Introduction

Methods

Participants

Data collection

Measurements

Statistical analysis

Ethics

Results

Patient characteristics

Clinician characteristics

Factors associated with underestimation vs. accurate estimation

Factors associated with overestimation vs. accurate estimation

Discussion

Conclusion

Declarations

References

Additional Declarations

Supplementary Files

Status:

Journal Publication

Version 1